Continental-scale drivers of soil microbial extracellular polymeric substances

Domain: chemistry
Published: 2026-03-02
Editorial outcome: major_revision

Abstract
Extracellular polymeric substances (EPS) are key microbial residues that contribute to soil organic carbon (SOC) and promote soil aggregation. Yet, their abundance and large-scale controls have only begun to be investigated. We conduct extensive soil sampling across a European transect spanning diverse climates, bedrocks, and land uses. Average soil EPS content is 956 ± 55 µg g-1 soil (n = 92 sites), with EPS-carbon (EPS-C) contributing 1.6 ± 0.1% to SOC. Bedrock influences EPS content, EPS-C contribution to SOC, and the EPS-C/microbial biomass carbon (MBC) ratio, whereas land use mainly affects the latter two. The EPS-C/MBC ratio is negatively correlated with microbial growth and carbon use efficiency, and increases under water deficit, while EPS increases with MBC, clay content, and exchangeable calcium. Our results demonstrate that EPS represents a functionally important microbial residue, regulated by climatic, edaphic, microbial, and land-use factors, with significant implications for soil carbon cycling and sequestration.

Introduction
Soil microbial extracellular polymeric substances (EPS) are essential components of the soil carbon (C) pool1, 2. In contrast to EPS, microbial necromass mainly consists of microbial cell wall fragments and is widely quantified using amino sugars as biomarkers3. They have been extensively investigated, are reasonably well understood3, 4, and contribute approximately 30-60% of the total soil organic carbon (SOC)3. However, EPS remains a largely overlooked C pool at regional scales and may play important functional roles in soil aggregation, microbial habitat formation, and short-term C dynamics1, 5. Its relationships with geological, land use, climatic, edaphic, plant, and microbial factors are not yet fully understood. EPS comprises a heterogeneous mixture of biopolymers (exoproteins, exopolysaccharides) targeted for their extracellular role and secreted by microorganisms that support them to resist environmental stresses and absorb nutrients and other resources5, 6. The primary components of EPS are polysaccharides (exopolysaccharides) and proteins (exoproteins)1, 6, 7. EPS polysaccharides are composed of neutral sugar, amino sugar, and sugar acid monomers, are highly viscous, and therefore facilitate the attachment of cells to the surfaces of soil particles8, 9. EPS proteins are comprised of proteinogenic amino acid monomers that perform more complex functions, such as providing structural and enzymatic functions and enabling cell-to-cell communications in response to environmental signals10. EPS polysaccharides are important components of biofilms, the strength and structural diversity of which are promoted by EPS proteins. Together, EPS polysaccharides and EPS proteins eventually embed microbial cells and consortia to form millimeter-thick biofilms in aquatic systems, while the extent of biofilm formation in soils is still debated8, 11, 12. Independent of the presence of soil biofilms, EPS plays multifunctional roles in soil ecosystems1, 13. EPS enhances water retention, mediates nutrient storage, and supports microbial resilience under environmental stress1. Beyond favourable effects of EPS on microbial performance, EPS contributes to SOC dynamics by serving as a microbial-derived direct C input and by promoting soil aggregation and mineral-organic associations, which are critical processes for physical and chemical stabilization of SOC6, 13. Furthermore, EPS facilitates microbial attachment to soil particles, potentially enhancing the association between microbial necromass and mineral surfaces following microbial death. Such interactions between EPS and other microbial residues may accelerate soil microbial-derived C stabilization and thus represent an additional, underexplored pathway through which EPS can promote long-term C storage. These diverse functions underscore the ecological relevance of EPS in structuring soils and regulating C cycling.

Given the potentially outstanding role of EPS for microbial function and SOC dynamics, it is interesting to note that quantitative measurements of soil EPS contents remain limited, and the lack of accepted EPS carbon (EPS-C) conversion factors leaves its contribution to SOC largely unknown. So far, the climatic and geological coverage of soil EPS measurements was relatively restricted, with studies confined to smaller-scale and/or local mechanistic questions, e.g., targeting soil EPS responses to current and legacy land use14, the interaction of land use and geology15, land reclamation16, tree plantation age17, 18, agricultural management19, 20, and root-soil aggregate interactions in forests and grasslands21, 22, 23. Therefore, studies on large-scale patterns and controls of EPS dynamics, including their effects on microbial necromass and SOC stabilization, are much needed.

The content of soil EPS may depend on (i) the microbial secretion of EPS and (ii) its association with soil particles6, 8, 13, as well as (iii) its decomposition and recycling. The secretion of EPS is typically stimulated under specific environmental conditions1. For instance, in soils rich in labile C, microorganisms tend to stimulate EPS production, which serves both as a structural matrix for effective application of extracellular enzymes and as a potential C resource for subsequent metabolism1, 15, 24. Moreover, when subjected to environmental stresses such as drought, high salinity, pH extremes, and C or nutrient limitations, microorganisms secrete EPS to retain water25, 26, 27, to provide ion and proton buffering, and to acquire nutrients, increasing the metabolite return on investment for the exoenzymes secreted28. Finally, as microbial communities expand, EPS secretion enhances cell adhesion on soil particles and helps protect against microbial competition5, 15. Collectively, these findings underscore that EPS secretion is governed by microbial growth and environmental stress1, soil properties, nutrient availability25, 26, 28, 29, and population-level survival strategies15.

Additionally, the content of soil EPS is influenced by its interactions with soil particles, which offer protection against degradation30, potentially affecting its contribution to the SOC pool. Soil mineral composition and particle size distribution can therefore affect how EPS associates with soil particles and aggregates. For instance, silt- and clay-rich soils can promote these associations, potentially reducing EPS accessibility to decomposition11. Furthermore, soil minerals such as Fe- and Al-oxyhydroxides and exchangeable Ca and Mg interact with EPS functional groups31, 32, promoting the association of EPS with soil particles. In conclusion, EPS secretion, its binding to soil particles, and its decomposition and recycling together determine the contribution of EPS to the SOC pool.

Various hypotheses have been proposed to explain the environmental controls on microbial EPS secretion and soil EPS content, but most have been tested based on laboratory or small-scale field studies. For example, Redmile-Gordon et al.14 showed that EPS acts as a transient binding agent, with protein levels higher in grasslands than in arable or fallow soils, likely reflecting land-use-driven shifts in microbial EPS secretion. However, forest soils—characterized by distinct microbial communities—were not included. Beyond microbial production, soil EPS content also depends on its interaction with soil minerals30, shaped by texture and mineralogy derived from bedrock. Soils formed from different bedrocks thus may vary in their capacity to bind with EPS13, though recently land use was shown to be the more important effector of soil EPS content than bedrock geochemistry in a tropical wet climate15. Despite increasing interest, no field study has systematically assessed the combined effects of land use and bedrock across varying climates on soil EPS. Large-scale investigations spanning forests, grasslands, and croplands on contrasting bedrock types across a broad climate gradient are therefore critical to disentangle the ecological and environmental influences on soil EPS-C pools.

Here, we conducted large-scale soil sampling on a transect that spanned ~5,500 km across the entire European continent, quantified EPS in soil samples from 92 different sites, and compiled a broad range of related environmental and biotic parameters (i.e., climate, plant, soil, and microbial factors). Thereby, this study addressed three major research questions: (1) What is the distribution of EPS content in soils along a European climate transect, and how do land use and bedrock types influence this distribution? (2) What is the contribution of EPS-C to the SOC pool, and what causes potential differences along a European climate transect? (3) Finally, how does the microbial EPS-C/MBC ratio change on a European climate transect, and how do environmental conditions such as C and nutrient availability, pH, and soil water deficit affect this ratio? By exploring these questions, we aim to gain a deeper understanding of the role of EPS across different soil ecosystems and its influence on soil biogeochemical processes.

Results
Soil EPS dynamics and drivers across bedrock and land-use types
Across the European transect, total soil EPS content (sum of EPS polysaccharides and EPS proteins) ranged from 149 to 2495 µg g-1 soil, with a grand mean of 956 ± 55 µg g-1 soil (SE; n = 92), higher than previously reported values (mean: 423 µg g-1 soil) (Figs. 1, 2; Supplementary Table 1; Supplementary Data 1). Bedrock type strongly influenced total EPS content, while land use had no significant effect (Figs. 2a, b; Supplementary Table 2). EPS content was significantly higher in soils on carbonate than on silicate and sediment bedrock, albeit the latter two did not differ significantly (Fig. 2a). Although not statistically significant, total EPS content appeared higher in grasslands than in croplands and woodlands (Fig. 2b).
To identify the major environmental and microbial drivers of soil EPS at this large scale, correlation analyses were performed, showing that EPS content was influenced by multiple factors, most strongly by soil physicochemical properties and microbial parameters (Fig. 2c).
Soil EPS content increased with mean annual precipitation (MAP), and showed weaker positive correlations with aridity index (ADI) and elevation, but was not significantly related to latitude, longitude, mean annual temperature (MAT), and potential evapotranspiration (PET) (Fig. 2c). Among plant parameters, EPS content increased with root nitrogen (N), weakly with fine root biomass (FRB), and decreased with root C/N (Fig. 2c). Among the soil properties, EPS content was strongly related to soil C and nutrients, showing a strong positive correlation with soil total nitrogen (TN), positive correlations with SOC, total phosphorus (TP), total organic phosphorus (TOPS), total dissolved nitrogen (TDN), exchangeable Ca2+ (Ca ), exchangeable Mg2+ (Mg ) and weak positive correlations with nitrate (NO -) and soil N/phosphorus (P) ratio, while there were no significant correlations with the soil C/N and C/P ratios, and dissolved organic carbon (DOC). Additionally, EPS content was not significantly correlated with soil pH (Supplementary Fig. 3), while it showed positive correlations with soil water holding capacity (WHC) and soil moisture content (SMC). Soil texture, minerals, and cation exchange capacity (CEC) also had strong effects on EPS content. The content of EPS increased with clay and silt content, was positively correlated with soil CEC, but showed no significant relationships with Fe and Al oxyhydroxides, and decreased with sand content (Fig. 2c). Among microbial parameters, EPS content increased with microbial biomass – including MBC, nitrogen (MBN), and phosphorus (MBP) – and decreased with the MBC/MBN ratio. EPS was positively correlated with microbial enzyme activity (exoglucanase-cellobiosidase (CEL), β-glucosidase (BG), and enzyme vector length (VectorL)) and with microbial biomass turnover time (MBT), strongly negatively correlated with microbial growth normalized to MBC (q ), and weakly negatively correlated with microbial carbon use efficiency (CUE). Other microbial parameters potentially linked to EPS formation, including nitrogen use efficiency (NUE), leucine aminopeptidase (LAP), and most PLFA-based microbial community composition metrics, were not significantly related to EPS (Fig. 2c). Supplementary Tables 8-10 provide additional results from linear models and linear mixed-effects models assessing the influence of bedrock, land-use types, environmental, and microbial factors on total EPS.

Drivers of specific soil EPS components
As the primary components of EPS, we investigated whether environmental and microbial drivers of EPS polysaccharides and EPS proteins followed congruent or different patterns. Statistical analysis revealed that bedrock and land use had distinct influences on EPS polysaccharides and EPS proteins across the European transect (Fig. 3; Supplementary Table 2). Specifically, EPS polysaccharides varied significantly with bedrock types (carbonate > silicate / sediment; Fig. 3a) but not with land use (Fig. 3b). Conversely, EPS proteins differed significantly across land use types (grassland > woodland / cropland; Fig. 3d), while showing no significant variation with bedrock (Fig. 3c).
Principal component analysis (PCA) and random forest analyses revealed broad similarities in environmental and microbial drivers of the two EPS components, i.e., microbial factors (MBN, MBC, q , VectorL, CEL, BG, and bacteria to fungi ratio (B/F)), plant traits (FRB and root C/N), climate (ADI), and soil nutrients (Ca , SOC, TP, and soil C/N) and clay (Fig. 4a). Both EPS compounds were strongly related to soil WHC (Fig. 4a). Notably, Ca , SOC, and MBN emerged as the most critical factors that significantly influenced EPS polysaccharides (Fig. 4b), while MBN, SOC (p = 0.059), and q were the most important drivers of EPS proteins (Fig. 4c). However, we also found distinct patterns among driving factors between EPS components: soil clay content and root C/N influenced EPS polysaccharides, while FRB and B/F affected EPS proteins (Fig. 4b, c). Supplementary Tables 11-16 provide additional results from linear models and linear mixed-effects models assessing the influence of bedrock, land-use types, environmental, and microbial factors on EPS polysaccharides and EPS proteins.

Contribution of EPS-C and microbial necromass to SOC
Across the European transect, soil EPS-C content ranged from 0.06 - 1.07 g C kg-1 soil, with an average of 0.41 ± 0.02 g C kg-1 soil (SE; n =92) (Fig. 5 a, b). Notably, EPS-C contributed 0.3 - 3.9% to the SOC, with average contributions of 1.6 ± 0.1% (Fig. 5c, d). The contributions of EPS-C to SOC varied significantly across bedrock and land use types (Fig. 5c, d; Supplementary Table 2). Across bedrock types, EPS-C contributions followed the pattern: carbonate / sediment > silicate (Fig. 5c). In terms of land use, EPS-C contributed 2.0% to SOC in croplands and grasslands, which was significantly higher than the 1.2% contribution in woodlands (Fig. 5d).
Furthermore, we found that across the European transect, microbial necromass carbon (MNC) contributed 20.9% to SOC, with bacterial necromass carbon (BNC) contributing 11.5%, and fungal necromass carbon (FNC) contributing 9.4% (Supplementary Fig. 7). The contribution of MNC to SOC was therefore nearly ten times that of EPS-C. In addition, notably strong positive correlations were observed among SOC, MBC, MNC, and EPS-C (Fig. 6).

Dynamics and drivers of the EPS-C/MBC ratio
Across the European transect, we observed significant variations in EPS-C/MBC ratios among soils from different bedrock and land-use types (Fig. 7a, b; Supplementary Table 2). EPS-C/MBC ratios declined as sediment / carbonate > silicate (Fig. 7a), while in terms of land use types, it was ranked as cropland / grassland > woodland (Fig. 7b).
Correlation analysis revealed significantly negative associations between EPS-C/MBC ratio and microbial factors (microbial growth (C ), CUE, acid phosphatase (AP), and q ) (Fig. 7c). Soil factors such as clay and silt content, and Ca positively affected EPS-C/MBC ratio while others were negatively associated such as soil C/N ratio and sand content (Fig. 7c). Further potential drivers such as climate factors (ADI), plant traits (FRB), soil factors (e.g., soil C/P ratio, SMC, and DOC), and microbial factors (MBC, MBP, MBC/MBN ratio, and β-xylosidase (BX)) showed weak negative correlations with the EPS-C/MBC ratio, while other soil factors (e.g., CEC) and microbial factors (e.g., MBT, MBN/MBP ratio, and VectorL) exhibited weak positive correlations with the EPS-C/MBC ratio (Fig. 7c). Correlations between EPS-C/MBC ratio and soil pH were significant (Supplementary Fig. 3b). Supplementary Tables 17-19 provide additional results from linear models and linear mixed-effects models assessing the influence of bedrock, land-use types, environmental, and microbial factors on EPS-C/MBC ratio.
To assess direct versus indirect effect pathways between environmental and microbial drivers and both soil EPS-C content and EPS-C/MBC ratio, we performed SESM analysis. Soil physicochemical variables were summarized as a composite factor derived from PC1 of a PCA (Fig. 8b; Supplementary Fig. 1a). Specifically, PC1 (soil) was positively loaded by the soil C/N ratio and near-zero positively loaded by SOC, while clay content and Ca had negative loadings. In the SEM, this composite soil factor showed a negative path coefficient to EPS-C, indicating that lower scores on this PCA-derived soil factor (i.e., higher clay, and Ca ; lower soil C/N ratio) were associated with higher EPS-C content (Fig. 8a). In contrast, the microbial composite factor, derived from PCA of CUE, C , q , and MBN (Fig. 8c; Supplementary Fig. 1b), exerted a direct positive effect on EPS-C/MBC ratio and a non-significant negative effect on EPS-C (Fig. 8a). In the PCA loading, C , q , and CUE had negative loadings on PC1 (microbial), while MBN had a near-zero positive loading. Thus, the SEM paths indicate that lower values of this PCA-derived microbial factor (i.e., higher CUE, C , and q ) were associated with lower EPS-C/MBC ratio. Additionally, plant factors (FRB) directly positively affected EPS-C. Climate factors (ADI) exerted direct effects as well, showing a significant positive impact on EPS-C but a negative impact on the EPS-C/MBC ratios. Land use type also directly influenced EPS-C. In contrast, bedrock affected the EPS-C only indirectly by shaping soil factors (Fig. 8a).

Methods
Site description
To investigate the distribution of EPS and its drivers on a continental scale, we sampled 92 sites across Europe (36º24 '45' N- 71º01 '56' N, 8º31 '56' W- 29º34 '60' E), spanning from the Mediterranean (Southern Spain) to the subarctic (Northern Norway), and from the Atlantic coast (Western Portugal) to the dry continental steppes (Eastern Romania). The sampled soils were distinct in soil parent material, soil type, land use and vegetation. Sampling sites were selected to represent the natural vegetation as defined in the “Map of the natural vegetation of Europe”59. Geographical and climatic data, including latitude, longitude, elevation, mean annual temperature (MAT), mean annual precipitation (MAP) and potential evapotranspiration (PET), were extracted for each site from the WorldClim database (v.1.4) at 100 m resolution. Bedrock information was obtained from the International Geological Map of Europe (IGME5000, 1:5,000,000)60, and dominant soil types were derived from the Soil Regions of the European Union and Adjacent Areas map (EUSR5000, 1:5,000,000)59. In brief, MAT of the sampling sites ranged from -3 to 18 ºC, while MAP ranged from 415 to ~1400 mm yr-1. An aridity index (ADI) was calculated as the ratio of MAP to mean annual PET61.

Sampling
Soil samples were taken from May to August 2017, at the peak of the vegetation season across a European climate transect. The sampled soils differed in terms of soil parent material, land use, and vegetation. At each site, samples of mineral topsoil (0-15 cm) were taken with a soil corer (5 cm). Each bulk soil sample consisted of five sub-samples taken at ~5 m distance from each other. These five sub-samples were composited and then sieved to give one mixed mineral soil sample per site. Therefore, no within-site replicates were analysed. Where possible, more than one and up to all three land uses (woodland/forest, grassland, and cropland) were sampled in close vicinity, termed a region or site cluster. In total, we sampled 92 mineral topsoils (92 sites) from 39 geographically distinct regions (a region characterized by the same climate and bedrock, but sites with different land use). In 23 regions (site clusters), we were able to sample soils from woodland (forest), grassland, and cropland areas in close proximity (Supplementary Data 1). Bedrock types were aggregated into three large groups for statistical analyses: carbonate (e.g., dolomite, limestone, and marl), sediment (e.g., flysch, molasse, till, and fluvial sand), and silicate (e.g., plutonic, igneous, and metamorphic formations). The soil samples were separated into aliquots, which were either air-dried or stored under moist conditions at 4 °C.

Characterization of soil, plant, and microbial properties
A comprehensive set of soil physicochemical, plant, and microbial parameters was used in the analyses, compiled from both previously published sources59 and unpublished datasets within the same project framework. Soil physicochemical properties were analyzed on either air-dried or fresh samples, depending on the parameter. Soil texture (sand, silt, and clay), cation exchange capacity (CEC), exchangeable Ca2+ (Ca ), and Mg2+ (Mg ) were determined on air-dried soils by the Austrian Agency for Health and Food Safety (AGES) according to European and international standards (ÖNORM). Fe oxyhydroxides and Al oxyhydroxides were determined on air-dried soils by extraction with acid ammonium oxalate (Fe and Al ) and Na-dithionite extracts (Fe and Al ) at the Institute of Soil Research (IBF, University of Natural Resources and Life Sciences, Vienna, Austria). Fe minus Fe represented Fe bound in crystalline oxyhydroxides (Fe ). Roots, collected during soil sieving, were washed and oven-dried at 60 °C to determine fine root biomass (FRB). Dried root and air-dried soil samples were ground and analyzed for root carbon (C) and nitrogen (N) contents, and for soil organic carbon (SOC) and total nitrogen (TN) using an elemental analyzer. Root phosphorus (P) was determined by dry ashing, acid extraction, and colorimetric measurement, and root C/N/P ratios were subsequently calculated. Soil pH was measured in water (1:5 (w:v)) using an ISFET pH sensor (Sentron, Leek, the Netherlands). Soil total P (TP) and inorganic P (TIP) were determined from 0.5 M H SO extracts of ignited and control samples, 2 4 with reactive phosphate quantified colorimetrically using malachite green. Organic P (TOP) was calculated as TP - TIP, and soil C/N/P ratios were subsequently calculated. Dissolved organic C (DOC) and total dissolved N (TDN) were measured in 1 M KCl extracts (1:5, w:v; 1 h) after filtration through ash-free cellulose filters (Whatman) using a TOC/TN analyzer (TOSC-VCPH/TNM-1, Shimadzu, Austria). Ammonium (NH +) and nitrate (NO -) were determined colorimetrically. Soil water holding capacity (WHC) was determined by saturating 10 g of field-moist soil with deionized water and allowing it to drain through an ash-free cellulose filter in a funnel for 2.5 h. Soil moisture content (SMC) was determined gravimetrically as the mass loss upon drying fresh soil.
Soil microbial community composition was analysed using phospholipid fatty acid (PLFA) analysis following Kaiser et al.62. Total lipids were extracted with chloroform-methanol-citrate buffer, and phospholipids were separated on silicic acid columns and converted to fatty acid methyl esters prior to gas chromatographic analysis. PLFA biomarkers were assigned to Gram-positive bacteria (GPB, i15:0, a15:0, i16:0, i17:0 and a17:0), Gram-negative bacteria (GNB, 18:1ω7, cy17:0, 16:1ω7, 16:1ω9, cy18:0, cy19:0 and 16:1ω5), fungi (18:2ω6,9, 18:1ω9 and 18:3ω3,6,9), and total bacteria (sum of Gram-positive and Gram-negative markers together with 18:1ω5, 17:0, 15:0, 17:1ω6 and 17:1ω7)62. Total microbial biomass was calculated as the sum of all detected PLFAs. Bacteria-to-fungi (B/F) and Gram-positive-to-Gram-negative (GPB/GNB) ratios were also calculated accordingly. Microbial process data, such as microbial growth (C ) and carbon use efficiency (CUE), exoenzymes, and microbial C, N, and P, were measured on fresh soils directly after collection. Specifically, microbial biomass carbon (MBC), nitrogen (MBN), and phosphorus (MBP) were determined via chloroform fumigation extraction63, from which the MBC/MBN/MBP ratios were calculated. Microbial nitrogen use efficiency (NUE) was calculated based on concurrent measurements of microbial growth and gross N mineralization rates64. CUE, C , growth normalized to microbial biomass carbon (q ), and microbial biomass turnover time (MBT) were estimated from measurements of MBC, basal respiration, and 18O incorporation into dsDNA65. Soil microbial necromass carbon (MNC), including fungal necromass carbon (FNC) and bacterial necromass carbon (BNC), was quantified using amino sugar biomarkers analysed by acid hydrolysis followed by 1-phenyl-3-methyl-5-pyrazolone (PMP) derivazation and ultra-high performance liquid chromatography (UPLC) coupled to Orbitrap high-resolution mass spectrometry (HRMS)46. Glucosamine and muramic acid were used as indicators of fungal and bacterial necromass, respectively. Hydrolytic enzyme activities were measured using microplate assays65, 66. β-glucosidase (BG), N-acetyl-β-glucosaminidase (NAG), leucine aminopeptidase (LAP), acid phosphatase (AP), cellobiosidase (CEL) and β-xylosidase (BX) were determined fluorometrically using 4-methylumbelliferone (MUB)- or 7-amino-4-methylcoumarin (AMC)-linked substrates. Phenoloxidase (POX) activity was measured colorimetrically using 0.4 mM ABTS (2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid)) at 420 nm. Enzyme activities were calculated from the increase in fluorescence or absorbance during incubation and expressed as nmol h⁻1 g⁻1 dry soil (or µmol h⁻1 g⁻1 dry soil for POX). Enzymatic vector length and angle were calculated based on enzyme stoichiometric ratios67.

Soil EPS analysis
Soil EPS (including polysaccharides and proteins) was extracted from air-dried soil samples in 2024 using cation exchange resin (CER)2. Soil EPS binds to negatively charged soil surfaces, such as clay minerals and organic matter, through electrostatic interactions involving Ca2+ bridging. CER, in its sodium form, exchanges its Na+ ions with these divalent cations, weakening Ca2+ bridging and releasing EPS from the soil matrix. This technique is highly efficient for the extraction of EPS and induces negligible cell lysis, yielding highly pure EPS fractions2, 44.
A preliminary experiment was conducted to optimize EPS extraction using different CER:soil ratios across soils varying in bedrock type and SOC content, showing that 1 g of air-dried soil with 10 g of CER provided a good balance for determining both EPS polysaccharides and EPS proteins (Supplementary Method 1; Supplementary Fig. 4). Before extraction, we also calculated the required amount of CER for each soil sample based on its SOC content following the method proposed by Redmile-Gordon et al.2. These calculations showed that 10 g CER per 1 g dry soil provided sufficient ion-exchange capacity even for the samples with the highest SOC levels, and importantly for soils with the highest exchangeable Ca2+ concentrations. Therefore, we applied this amount uniformly across all soils to ensure methodological consistency across SOC-rich and SOC-poor soils and limestone and non-limestone soils.
In the formal EPS extraction procedure, the extraction buffer was prepared, the pH adjusted to 7.4, and the solution cooled to 4 °C in advance. CER (Amberlite™ IR120 Ion Exchange Resin, Na+ form, 15-50 mesh, Sigma Aldrich) was thoroughly hydrated and washed using the extraction buffer. Aliquots of air-dried soils (1 g) were weighed into 50 ml centrifuge tubes and amended with 25 ml 10 mM CaCl 2 solution. The suspension was then shaken gently for 30 min, and centrifuged at 4 °C at 4000 g for 30 min, after which the supernatant was carefully poured off to remove interfering extractable non-EPS microbial products such as free sugars and amino acids. Subsequently, EPS was extracted by adding 25 ml of extraction buffer and 10 g CER, and the mixture was shaken for 2 h before centrifugation at 4 °C at 4000 g for 30 min. The supernatant was then filtered through 0.45 µm filters (VWR® Syringe Filters, Nylon, 25 mm, Avantor), and the obtained solution was stored at 4 °C and used for the determination of EPS polysaccharides and EPS proteins within 4 d.
EPS polysaccharides were measured by acid hydrolysis and anthrone reaction using glucose as a standard68. The color reagent was produced by dissolving 0.2 g anthrone in 100 ml concentrated H SO 2 4 (previously cooled to 0 °C). For colorimetric assays, 200 µl of sample, standard, or blank (MQ) was added to 10 ml glass tubes, followed by the addition of 1 ml anthrone reagent. The mixture was then mixed well and heated to 100 °C in a water bath for 10 min. After rapid cooling to room temperature, the absorbance was measured at a wavelength of 625 nm.
EPS proteins were determined by a modified Lowry method69, based on Cu-binding to polypeptides and the Folin-Ciocalteu reaction, with modifications to account for humic compound interferences in soil extracts. Bovine serum protein was used as the standard. Samples, standards, and blanks (MQ) were pipetted into microtiter plates, mixed with copper-containing or copper-free NaK tartrate/Na CO -NaOH 2 3 buffer for 10 min, supplemented with Folin-Ciocalteu reagent, and after 30 min, EPS protein absorbance was measured at a wavelength of 750 nm.
Total EPS was approximated as the sum of EPS polysaccharides and EPS proteins70, 71. This approximation is based on the fact that EPS polysaccharides and EPS proteins are the major components of microbial EPS, together contributing approximately 90% of total EPS33, 34. This approach has been widely employed for estimating total EPS levels. However, we acknowledge that this method may slightly overestimate total EPS due to potential overlaps between components—for example, measurement of glycoproteins33, which are partially detected in both colorimetric protein and polysaccharide assays. Despite this, the potential bias is likely small and considered acceptable for comparative purposes across sites. The EPS data used in this study have been provided as Supplementary Data 1.

Estimation of EPS-C
The C content of EPS polysaccharides (39.1% C) was estimated by elemental analysis in our laboratory as the average of four microbial and plant exopolysaccharide standards, including hyaluronic acid (37.5% C), xylan (40.5% C), pectin (38.3% C), and arabinogalactan (40.2% C).
The C content of EPS proteins (50.7% C) was estimated from the global average protein N content (16% N), multiplied by a weighted mean C/N ratio of proteinogenic amino acids. Given that individual proteinogenic amino acids show variable C/N ratios, ranging from 1.5:1 to 9:1, and since proteins show marked deviations in their amino acid composition, we refrained from the use of a mean proteinogenic amino acid C/N ratio. Instead, we here applied a weighted mean amino acid C/N ratio calculated from the amino acid sequences of all genome-encoded polypeptides comprising the full proteome of the yeast Saccharomyces cerevisiae as an environmental microbe representative72. This gives a proteome-average of 5.03 mol C and 1.36 mol N per mol protein-derived amino acids72, a molar C/N ratio of 3.70 (5.03 / 1.36 = 3.70), and a mass-based C/N ratio of 3.17 ((5.03 mol C × 12) / (1.36 mol N × 14) = 3.17). Using a global average protein N content of 16% by mass73, 74, and a weighted mass-based amino acid C/N in microbial proteins of 3.17, the corresponding protein C content can be approximated by formula (1):
protein C content [%C] = 16.0 (%N)×3.17 (C/N) = 50.7% (1)
These conversion factors were applied to measured EPS polysaccharide and EPS protein contents (in mg g-1 soil dw) to estimate their respective C contents.
The final formula (2) for summed EPS-C is:
EPS−C ( g C kg−1 soil dw) = (EPS polysaccharides × 39.1%)+ (EPS proteins × 50.7%) (2)
which provides an approximate estimate based on representative C content. To our knowledge, this represents an important attempt to quantify soil EPS-C contents, as such estimations were previously hindered by the lack of representative data on the C content of EPS components. In this study, we addressed this gap by determining average C content values from standard compounds representative of microbial EPS polysaccharides and by calculating Nprotein C from proteome-averaged protein C/N ratios and published global protein N contents. While these estimates provide a useful approximation, we acknowledge that they do not fully capture the chemical diversity of EPS in soils. Based on EPS-C, we calculated the ratio of EPS-C to MBC. This EPS-C/MBC ratio has previously been termed EPS production efficiency, referring to the amount of EPS secreted by microorganisms in soils15. However, post-production processes, including EPS-soil associations and decomposition, can modify this ratio. While the concept is useful for characterizing short-term microbial EPS responses under conditions where these processes are negligible51, in natural soils, the metric is more appropriately referred to as the EPS-C/MBC ratio and should be interpreted with caution. Additionally, we calculated the EPS-C/SOC ratio to represent the contribution of EPS-C to total SOC.

Statistical analyses
Statistical analyses were performed and visualized using R version 4.1.275. One-way ANOVA was applied to examine the effects of bedrock and land use on the target EPS variables, namely total soil EPS content, EPS polysaccharide and EPS protein contents, the EPS protein/EPS polysaccharide ratio (Supplementary Fig. 5), EPS-C content, the EPS-C/SOC ratio, and EPS-C/MBC ratio. Subsequently, we used linear regression models to analyze the relationships between EPS variables (total soil EPS content, EPS polysaccharide content, EPS protein content, and EPS-C/MBC ratio) and environmental and microbial factors. Three models were applied: (1) a simple linear regression to assess the effect of environmental and microbial factors on EPS variables, (2) a multiple linear regression with an interaction term to examine the combined effects of environmental and microbial factors and land use type, and (3) another multiple linear regression to evaluate the interaction between environmental and microbial factors and bedrock type (lm function in R). To assess the influence of environmental and microbial variables on EPS dynamics, we performed Spearman’s correlation analysis. Moreover, principal component analysis (PCA) was employed to examine the impacts of environmental and microbial factors on EPS polysaccharides and EPS proteins (R package stats). Random forest models were used to rank the importance of controlling factors of EPS polysaccharides, EPS proteins, EPS-C, EPS-C/SOC, and EPS-C/MBC ratios (Supplementary Fig. 6) (R package randomForest). We examined the relationships between EPS-C, MNC, MBC, and SOC by fitting linear regressions to ln-transformed variables using the lm function in R. To investigate the effects of bedrock and land use type on environmental and microbial factors, we performed two-way ANOVA for each environmental and microbial variable. Variance partitioning analysis (VPA) was then conducted to quantify the relative contributions of bedrock and land use type to the variation in these factors. To evaluate the effects of bedrock, land use type, environmental and microbial factors on soil EPS-C content and the EPS-C/MBC ratio, we performed structural equation modeling (SEM) analysis (R package lavaan). Before constructing the SEM, we first examined collinearity among all environmental variables and removed highly correlated factors to reduce multicollinearity. After this selection process, the retained variables included ADI, FRB, MBN, C , q , CUE, SOC, clay content, soil C/N, and Ca . The environmental variables were grouped into four categories: climate (ADI), plant (FRB), microbe, and soil. Among them, SOC, soil clay content, soil C/N, and Ca were combined into a soil composite variable, while MBN, C , q , and CUE were combined into a microbial composite variable, for both using PCA. We used the first principal component (PC1) to represent each composite variable, as it captured a substantial proportion of the variance (51.3% for soil, 62.5% for microbes) (Supplementary Fig. 1). Using this categorization, we developed an SEM model to explore how these four environmental and microbial components, along with bedrock type and land use, may directly or indirectly influence EPS-C content and EPS-C/MBC ratio. Model fit was evaluated using multiple fit indices, including the Chi-square test (χ²), Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), Standardized Root Mean Square Residual (SRMR), and Akaike Information Criterion (AIC). In the best-fitting model, we calculated direct and indirect pathway coefficients to determine the key drivers of EPS-C/MBC ratio and EPS-C variation across climatic, geological, and land-use gradients.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This impactful and interesting study is centred in an emerging area of great relevance for soil health and climate science. Understanding the drivers of soil microbial EPS in Europe (continental scale) is an important step forwards in understanding the controls and relevance of this functional pool of soil C. The abstract, methods, and results are well written in the main. However, there are a few comments which need attention before publication, and I would not hesitate to recommend publication if these were resolved. Most importantly, the authors need to resolve a current conflict in their original manuscript: 1) acknowledging decomposition and stabilisation occur, but 2) confounding this within the (unnecessary) assumption that the observed EPS-C/MBC ratio = “EPS production efficiency”. This is easily resolved. Explanation: The processes of decomposition and stabilisation occur after production, and are therefore potentially independent of the EPS production efficiency. Therefore, the units used throughout the manuscript (EPS-C/MBC) require limiting to this unit, and not interpreting as “EPS production efficiency”. This change complements the thinking presented elsewhere in the manuscript (e.g line 323) - clarifying that the EPS pool measured using the standard approach (CER) is transient (subject to decomposition and stabilisation), as expected from i) established understanding on the nature of biofilms and EPS13, and ii) as previously observed in grassland, cultivated, and fallow soils16 Nonetheless, as revealed in the present study: EPS is still very important as a (direct) carbon pool in its own right, and contributes manifold (indirect) effects relevant for C stabilisation in soil, as already communicated clearly in lines: 441-446. Specific comments: Line 25-26, This sentence is vague. Many studies have successfully rejected various null hypotheses and ‘highly limited’ can suggest poor (when I believe ‘scarce’ was meant). I suggest the authors keep to the main subject of the study (EPS-C and EPS-C/MBC ratio) and replace this sentence with “However, systematic evaluation of this claim has yet to be reported.” Line 27, unnecessary preamble. I suggest to start the sentence at “We conducted extensive soil sampling…” Line 31 (and throughout manuscript - besides noted exceptions): “EPS production efficiency” should be independent of decomposition or stabilisation (as stated on Line 323). The EPS in these natural soils (presumably at approximate equilibrium) are subject to unknown and contrasting decomposition and stabilisation processes. Please present all as “EPS- C/MBC ratio” which more accurately reflects the measurements made. Line 42-43: it is circular to explain EPS accumulation by the compound EPS-C/MBC ratio. While it would not be circular to say accumulation was governed by EPS production efficiency (suggesting decomposition and stabilisation were negligible, or not variable) this is not what was measured. Line 43: replace “promoting” with “thought to promote” Introduction Line 63: meaning of “backbone” is unclear. This would suggest imparting physical strength but that is a role more typical of EPS proteins, please describe in clear terms. Line 72: please revise “tested” to “reported”. Line 76-77: EPS contribution to SOC depends on more than this: both stable and unstable. Replace “contribution” with “stabilisation”. Only long-term stable SOC relies on EPS stabilisation (not measured here). Reference 16 showed that stabilised EPS (persisting in soil for more than 2.5 years) was not extractable using the CER method. The fraction measured in the current study also represents non-stabilised EPS (as the method was intended 39). Stabilised, and/or partly decomposed materials are altered to the point at which they become difficult to characterise and quantify. Line 79: please replace “and is calculated as EPS” with “and was calculated as EPS” to accurately reflect the cited works 17, 48 Line 80: Please insert the following sentence before “For instance” to clarify [if the authors agree?] “However, we assume variable stabilisation and decomposition processes occur after EPS production. Thus while “EPS production efficiency” is a useful concept for characterising short-term EPS responses of the soil microbial biomass (where stabilisation/decomposition processes are assumed to be negligible)48 in studies of natural soils in comparative equilibrium (with time for soil-specific stabilisation and decomposition processes to occur) we present this metric simply as the EPS:MBC ratio. This not only represents the current state of equilibrium more accurately, but is consistent with the findings that current methods of soil EPS measurement (by CER extraction) do not quantify the decomposed or stabilised EPS fractions remaining after 2.5 years or more, and instead represent a transient -but more active- fraction of SOC16 Lines 80-86 continue smoothly: illustrating the point further. Except for: Line 80 “nutrient-rich” is vague. EPS production is known to depend on C availability 7, 17, 48 . Please re-examine and replace “nutrient-rich soil” with “soils rich in labile C”. Line 82: what is “high microbial biomass”? The point missed here is that EPS can be produced without large increases in microbial biomass to acquire nutrients7, 17, 48. Please edit Line 81 to make clear: “For instance, in soils with free labile C, microorganisms tend to stimulate EPS production, serving as both a template for effective application of enzymes, and as a potential carbon source for subsequent metabolism7, 17, 48 Lines 81-83: accordingly, please delete the conflicting sentence which follows at Lines 81-83. (The text then leads on smoothly to the next good statement at lines 83-85). Line 118: something wrong here. Please rewrite as “and in the latter case, what causes potential differences at the continental scale” if I understand correctly? Line 120: please replace EPS production efficiency with simple EPS/MBC units (as with rest of manuscript) (I advise a full search of all figures and tables too). Line 251: please replace EPS production efficiency in heading. 276-277: This is circular. Of course EPS-C scales positively with EPS-C/MBC. Please remove. Figure 7: Axes are labelled correctly, titles and captions need production efficiency removing. Figure 8: titles and captions need production efficiency removing. 322-323: Correct. Generation = production, so efficiency of EPS production is best not inferred from EPS and MBC concentrations in natural soils (or soils incubated for a long time). See comments above. 326-327: There is no evidence in the literature that stabilised EPS is extractable using CER. The evidence suggests the opposite is true16, 48. Perhaps the high EPS concentrations in carbonate soils suggests instead that carbonate soils (with their naturally improved structural stability, porosity, and heterogeneity) stabilise less EPS: representing instead reduced stabilisation or reduced “loss” to organo-mineral associations. This would make sense logically as a more homogenous distribution of (structureless) fine minerals (from non-carbonate soils) is likely to increase the formation of “stabilised” organo-mineral associations, and soil microbial communities do well in more structured media that can be expected from carbonate soils, with EPS being positively correlated with biodiversityX, Y (Wu et al., 2019; Zhang et al., 2024) Would the authors concur? Recommended references X, Y: Wu, Y., Cai, P., Jing, X., Niu, X., Ji, D., Ashry, N.M., Gao, C. and Huang, Q. (2019) Soil biofilm formation enhances microbial community diversity and metabolic activity. Environment International, 132, 105116.CrossRefGoogle ScholarPubMed Wu, Y., Cai, P., Zhang, M., Qu, C., Huang, Q., and Cai, P. (2024). Microbial extracellular polymeric substances (EPS) in soil: From interfacial behaviour to ecological multifunctionality. Geo-Bio Interfaces, 1, 2024. DOI: 10.1180/gbi.2024.4. Line 333-335: As above, this is counter-intuitive, and likely arises from the previous view that stabilised EPS is extracted with CER (when existing evidence and theory suggests it is not). Please change this statement to also reflect the rationale above. Line 335: “Sedimentary rocks can be rich…” Line 340: “properties thought to promote…” Line 367: “possibly due to relaxed…” Line 376-379: to refine and shorten the narrative here I would recommend reconciling the previously mentioned literature in context. I suggest replacing the unnecessary sentence: “Nevertheless, these microbial diversity aspects were not effectively investigated in this study and warrant further exploration in the future”. AND In conclusion, it is the interplay….” (repetition of land-use)(nonspecific EPS fractions). With “While microbial diversity was not investigated in this study, in accordance with investigations of legacy vs current management effects on EPS16, it is primarily the interplay between plant inputs and anthropogenic management which causes these differences in total and proteinaceous EPS concentrations”. Line 385: “Stabilization” was not measured, please remove. Lines 385-388: Accordingly, please refine, or remove ‘stabilization’ from this sentence. Line 422: Please insert a full stop after “on a continental scale”. Line 422: Please delete “which is mainly due to differences in their lability or stability” and deal with the main known artefacts first. We do not yet know how much of either fraction is stabilized in soils. For a more conservative assessment, please insert “Incomplete extraction of EPS partly explains the difference between MNC and EPS-C observed here. Perhaps more importantly, amino sugar biomarkers do not exclusively represent necromass [reference Salas et al]. GalN for example can be found in substantial concentrations in plant residues, and other non-necromass materials, even EPS itself [reference Salas et al]. Therefore, while measures of EPS-C are understood to be underestimates, measures of MNC are known to be overestimates and perhaps with a larger margin for error and variability. This means that while on face value our results suggest that MNC was the larger pool of C, true values might be comparable. More research is needed to elucidate with confidence whether EPS-C or MNC contributes more to stable SOC formation. Nonetheless, our data for soils sampled at the continental scale show that both pools are important for (direct) carbon storage in soils – with EPS-C having been largely overlooked until now. For information: From Salas (Salas et al., 2024): “Galactosamine (GalN) and mannosamine (ManN) are nonspecific amino sugars which can be found in plants (Indorf et al., 2011), fungal cell walls (Beauvais and Latgé, 2018), EPS of bacteria (Caruso et al., 2018; Cheah and Chan, 2022; Vaningelgem et al., 2004), and in the cell envelope of some archaeal species (Albers and Meyer, 2011). Line 424: Please start new paragraph with “EPS is an active pool that is…” Line 428-429: Please delete speculation “This passivity makes the contribution of MNC significantly higher than EPS-C” There is no soils data available to confirm or deny this. Stabilization of EPS in soils is not yet understood, and certainly not measured/reported. Line 448: Please change title to reflect content - removing reference to EPS production efficiency, and instead reflect Drivers of EPS-C/MBC ratio, and EPS accumulation. Line 449: To more accurately reflect the cited work, please change first line regarding reference 48 to: Changes in short-term microbial EPS production efficiency was previously calculated by standardizing soil EPS concentrations to concentrations of soil microbial ATP 48. Line 451: Insert “However,” before “as mentioned above” 453: Please replace this sentence with “Distinct bedrock and land-use types have shaped diverse ecological environments, and no doubt influenced decomposition and accumulation of EPS” . 454: Before “a more detailed…” please insert “Therefore, we present EPS-C/MBC ratios “as is” without inferring EPS production efficiency”. The rest of the paragraph should now flow smoothly. Line 475: “Given the limited labile C…” Lines 480-482: please simplify and abbreviate this circular sentence Line 480-484: please reconsider and present in context of Bölscher et al., 2024: Bölscher, T., Vogel, C., Olagoke, F.K., Meurer, K.H.E., Herrmann, A.M., Colombi, T., Brunn, M., and Domeignoz-Horta, L.A. (2024). Beyond growth: The significance of non-growth anabolism for microbial carbon-use efficiency in the light of soil carbon stabilisation. Soil Biology and Biochemistry, 193, 109400. DOI: 10.1016/j.soilbio.2024.109400 487-489: I do not believe the evidence is strong enough to support this (complex) statement which seems to run counter to established understanding, please remove, or if the authors feel this is vital, contest this request? 487: Please replace the sentence here with information consistent with the referenced works “This trade-off means that C investment into EPS can only be maintained if sufficient labile C is available 17, 48” (Note that labile C cannot be inferred from SOC). 490: This bold statement may apply to the investigated soils, but is too sweeping as a universal statement. I urge the authors to reconsider, or simply remove. 492: This is clearly a mistake. Please remove this line and finish the paragraph as the rest (to line 494) is repetition/not necessary. 508: please remove “stabilization” 510: replace “can assist” with “may assist” 511: please delete “enforcing” 514: change ‘production efficiency’ 516-517: “Essential” is subjective and a little strong. For balance, please replace the sentence “it is essential to improve…” with “Addressing both the underestimations of EPS, and the overestimations of necromass respectively achieved by extraction will be important in clarifying our understanding of these formative carbon pools. 584: please remove “s” from “resins”. The rest of the method section looks good! Thank-you for all the hard work that went into this interesting and very useful manuscript. Best wishes and regards, Dr. Marc Redmile-Gordon", "reviewer_2": "Review by Stefano Manzoni, Stockholm University The manuscript by Ke Shi and co-workers explores spatial variations in extracellular polymeric substances (EPS) across Europe. This is a timely topic, as EPS plays important roles in modulating microbial activity in soils, with potential consequences for carbon and nutrient cycling. EPS spatial patterns and their drivers are largely unknown, so this is a welcome contribution. I should add that my background is in engineering (and modelling) and I don’t feel I can evaluate the methodology developed for EPS analysis. Therefore, my review focuses on conceptual aspects and data analysis. Overall, this is a well-written manuscript (though I would suggest some changes especially in the Discussion—see detailed comments below), with a clear structure and neatly-presented results. I like the progression from simple soil groupings (by land use or geology) to more detailed analyses of EPS dependence on various climatic, soil, and biological predictors. Nevertheless, I have some (relatively minor) comments on the interpretation the results. Main comments EPS production efficiency is defined as the ratio of EPS carbon (EPS-C) to microbial biomass carbon (MB-C). In my view, this is not a production efficiency, which would be rather defined as a rate of EPS production per unit microbial growth (or carbon uptake). My impression is that calling the EPS-C/MB-C ratio ‘production efficiency’ can be misleading. Indeed, some of the interpretations of this ratio in the Discussion mix up aspects related to EPS production and decay, which I agree are both important. I suggest to change the terminology to ‘biomass specific EPS’ or something along those lines. For example, in L276-277 it is stated that ‘EPS production efficiency promotes EPS accumulation’, but the data only indicate that EPS and EPS per unit biomass are correlated, suggesting that microbial biomass does not affect much the variation in EPS (if I interpret correctly). I agree with the statement in L322, which points to EPS as result of production and decay. But then the following statements introduce some confusion by interpreting production efficiency as the result of production and decay—I would clarify this part of the Discussion. I struggle to reconcile the function of EPS and the activity of extracellular enzymes. Are extracellular enzymes targeting EPS? This is a general comment, and not meant to criticize this work—still, here both enzymatic activity and EPS are measured, raising the question as to how the two interact in this dataset. The activity of some enzymes appears to be positively correlated with EPS contents, suggesting that microbes produce both and that enzymes do not affect negatively EPS (or the negative interaction is less strong than the coordinated production). Would it be worth discussing these interactions? Statistical analyses: even random forest approaches handle well collinearity, some of the variables included are very strongly correlated, so I wonder results would be more robust or easier to explain by selecting variables a bit more before running the random forest model and evaluating the importance rankings. Moreover, it is not clear how PC1 and PC2 were combined (L658-660). Data availability: it would be useful to be able to access the data in an open access repository. Other comments General: EPS is expressed as carbon mass per unit mass of soil, so I would call it ‘content’ (mass/mass ratio) rather than ‘concentration’ (mass/volume ratio) (McNaught, A.D., Wilkinson, A., 1997. IUPAC Compendium of Chemical Terminology, Blackwell Scientific Publications). I realize the terminology in the literature is inconsistent to this regard, so I do not feel strongly in either direction. Section 2.1: please define acronyms in the Results section, otherwise it is hard to read the text while continuously flipping pages to get to the definitions in the Methods. Figure 2: this figure is very dense of information, so I wonder if it could be simplified e.g., by removing the correlation heatmap for the ratio of EPS polysaccharide to EPS protein. I might have missed the importance of this ratio (I think it is only briefly mentioned in the Discussion), and in any case it does not seem to be highly correlated with many drivers. Figure 8: ‘bedrock’ text is not visible (black on black). L211 and L417: where is the evidence of the strong association between WHC and EPS shown? WHC does not appear among the highly ranked drivers. L319: was the methodology to estimate EPS in previous papers the same as used here? Can different measurement approaches explain the differences? L329: the cited article compared two soils only, so I wonder if the evidence that in soils originated from sedimentary rocks microbes are more adapted to decompose EPS is really strong and worth highlighting here in the Discussion (but admittedly I only scanned the cited article…) L368-369: alternatively, low MB-C can be linked to depleted soil organic matter or degraded soil after intensive agricultural practices. L398: rather than ‘contents’ I would call these ‘fractions’ (mass or EPS per unit mass of soil organic carbon). L400-404: this material was reported in the Methods and does not add much to the Discussion. L416: not clear what ‘amplifying effect’ means. L420: suggested change ‘climate change effects in agricultural systems’ L426-427: please add rough time scales for decomposition of EPS and microbial necromass, as these statements are now quite vague. L463: aridity is not a measure of drought severity or frequency of occurrence; to discuss drought effects, perhaps consider a climatic index that describe the intensity and/or frequency of dry periods. L489-492: the logic here is not clear—you start by pointing to a difference between aquatic and terrestrial systems, but then you conclude that carbon and nutrient limitation promote EPS production in both. L493-494: I did not understand how exoenzymes are related to the previous sentences on EPS. L518: I agree this would be great to actually estimate EPS production rates. Supplementary information: it would be helpful to provide captions of the supplementary Excel spreadsheets after the statement: ‘Tables S3-S14 are provided as an attached Excel file’. If data is not available in an open access repository, perhaps it could be included as supplementary information.", "reviewer_3": "Overall, the authors tackle an interesting topic which highly discussed within the community. However, in my point of view that authors do not help in going a step further. Please see my comments below. There is no questioning of the data in relation to a mechanistic understanding. In my opinion, the authors should have an idea of possible connections, which they then test in order to really take a step towards a better understanding. Everything was related to everything, but I miss the mechanistic idea behind it and it´s explanation. It would be better if the authors state clear hypothesis and test them. Furthermore, I have several doubts in terms of the methodology used. Some examples In the methodology section it is not becoming clear, which data have been taken from other studies and which data were analyzed on which kind of samples (Stored over how long!?) with which kind of purpose, several methods are just mentioned and the methodology is just referenced. But as a reader I expect to find the most important information within the paper. As the authors did EPS extractions on dry soil stored for an unknown period of time between 2017 and 2025, which I would highly question to produce the same results as other studies of EPS usually extracting EPS from fresh soil samples (could be one reason why the authors gained higher EPS concentrations!?), I am also questioning how and under which conditions the other data have been gained, e.g. CUE!? Same with the turnover time (microbial biomass turnover time) – how was determined on the sample taken along the transect and why was it related to EPS – what is the expectation behind? Furthermore, important calculations such as EPS-C is not described in detail – but used as a kind of indicator for EPS stabilization or accumulation (all of the terms used vague without clear definition). Since the calculation is not clearly explained in the method section, it feels to me as if the authors interpret the concentration as one or the other, depending on their discretion - as it suits the story better. Overall, the authors draw conclusions that they do not prove and rely on speculation and, force and back correlation. In addition, they use words without defining them and defining their analyses and are therefore appearing very very vague. Specific comments: Abstract: Line 24-25: EPS is part of the SOC, or? What do you want to say in regard to the “contribution”? Specifically, as you relate to it within the next sentence. Line 26-27: At that point in time it is not clear to which theories you refer too. Please rewrite. What is the specific knowledge gap you want to fulfill, “contribution” to SOC storage – drivers/controls of EPS? Line 29: Do you think that large scale controls matter for EPS? What is meant here by large-scale controls? Line 42: Unclear, what the authors mean with EPS accumulation!? Include as for EPS production efficiency… I don´t think that prompted is the right verb here – rewrite Line45: In my opinion the authors should not write “critical component of the soil-stable C pool” – as at least to my knowledge it is not proven that it is part of the soil-stable C pool – and the authors do not prove that either in their manuscript – rewriting necessary Introduction: Line 50 “elements” - remove by components Line 52-53: When I came across the number of 30-60% of SOC for amino sugars, is a contribution of 1.6% as mentioned for EPS substantial? Line 55: “a natural mixed polymer” – as I understood EPS composition, it is composed by a variety of different constituents – please adapt Line 70: I would wish that the authors elaborate a bit more on the “potential outstanding role of EPS… for SOC dynamics…” it is mentioned for the microbial functioning but for SOC dynamics it remains unclear to me at that point in time, specifically if their existence is debated overall in soil. That points need more preparation in my point of view, specifically if that is a main topic for the whole manuscript. Line 72: In regard of the existing literature the authors should check the current literature a bit stronger – e.g. Zhang et al. 2023 Chemical geology a whole table summarizing studies of EPS measurements from different soil types, including different land uses as well. Line 74-75: The authors should introduce microbial necromass in regard to the before mentioned cellular and extracellular residues. Please better pave the way why EPS could/should effect necromass - it is not becoming clear to me where the differences between the components are. Line 76-77: Is this statement assumed or verified by the papers referenced? I screened the article shortly and I could find a prove of it – Please be as precise as possible in your statements … throughout the manuscript and adapt accordingly. Line 87-95: Repetitive – can be more condensed and targeted Line 97: As indicated beforehand, there is no prove of long-term preservation of EPS in soils – please add the prove to be able to make that statement or adapt accordingly Screened shortly - Craig et al. did not include EPS measurements and the article by Chenu – no prove of preservation – assumption due was done due to the formed structures… and that needs be cleared up…. Line 106: The authors need to clarify for my better understanding what they mean by “accumulation” of EPS – are the authors using it simultaneously for preservation, stabilization and why do the authors think so…. EPS are from their composition relatively easy to degrade (proteins / sugars) – I would assume that EPS occurrence in soils is quite dynamic (as microbes use it as well as nutrient storage), so why an accumulation!? Terms need to be clarified. Line 107-108: What is the relation of the reference to the sentence? – it's starting to get exhausting – the authors studied one bedrock – what do the authors want to say – and is it really the best reference? 105-111: It would be preferred if the authors stated hypotheses which they tested in their study instead of saying that there are several out there. What specific hypotheses and procedures (compared to the other studies) guided their science? – What is new? Line 113: Does that mean that the samples were stored from this study frozen? Line 115-116: “What is the distribution of EPS on global scale” – this question is not well prepared in my point of view. I would assume that the EPS concentrations and compositions change with the microbes present in soil and their abundance – probably major differences on the small scale – so what would be the gain of information from a global distribution? Line 118-119: Again I don´t get the specification on the continental scale – needs clarification! Results: Line 136-137: What was analyzed, why and what was the result? Instead of referring that more detailed analysis can be found in the supplement…. Line 139: What is the soil total EPS? Why did the authors include it? is it sound to just sum up sugars and proteins? Could they not overlap? Please elaborate on that! Line 145: turnover time!? Turnover time of what!? Same with the figures – clear that up! Line 139-147: Instead of writing that you related everything to everything – it would be good if the authors stick to what they expected and what they found. A sentence over 9 line without any information – move to methods By the way, Ca and Mg are nutrients and not really soil minerals! Line 196-198: Might that be due to the EPS extraction method. There also different extraction method? Line 211: The authors should be bit careful in their statements. For me it is not becoming clear how the authors come from a correlation to the guess that “indicating that EPS promotes soil water holding capacity more than bulk SOC or texture” – please revise or explain Wild guesses and interpretations belong in the discussion – move it. Line 227-228: Unclear how this numbers have been generated! Line 235-237: Could it be that the authors extracted necromass, due to the soil storage and EPS extraction from dry soil? Line 237-239: Interpretation into the discussion Line 267: How did the authors investigate EPS stabilization!? Line 268-270: Sorry, I don´t get it. Ca was positively correlated with EPS and now it has a negative effect on EPS-C!? Clarify! Heatmap of EPS driving factors – for both EPS polysaccharides and proteins compared to SEM? – to me it makes no sense The authors base all of the presented data on EPS concentrations determined at one point in time. How was an EPS-C accumulation or stabilization determined? As it is not clearily Line 270: Which kind of expectations? And what do the authors mean by lower PC (soil) values? Line 276-277: refer to the data Discussion: It would be overall better if the authors stick to their data and what they can prove or reject instead of wild interpretations and assumptions! Line 309: The author don´t do a spatial analysis, so please be precise and write that the study has been conducted along a transect (not even covering Europe, but just some parts see Map of Noll et al). Clarify! Line 315-316: See my comment above – the authors overlooked quite some studies…. Line 319-320: Maybe due to differences in EPS extraction from dry/wet soil and storage and EPS polysaccharide determinations!? Please include If referring to explanations of different studies (I assume that previous studies can be checked in more detail in regard to your studied soils (ADI, carbonates and SOC – for example to check if your message can be underpinned by the other studies or not, instead of referring to a bunch of potential differences without a closer look, which is not advancing our knowledge. Line 322-323: Ok, and now go a step further – what does that mean for your interpretations!? Formatting of the reference! Line 326-327: The authors should elaborate a bit more on their assumption. Line 337-339: But an overall higher microbial biomass would also mean more potential EPS producers, or? The more MBC the more EPS-C see your own figure – clarify Line 339-341: To be able to follow your train of thoughts I would like to check the statement that the soils developed on sediment bedrock “were intermediate in properties promoting EPS stabilization” – I guess meaning low clay, low silt, Ca and Fe contents – that’s what I would like to prove it. Line 335fff: I would assume that the larger difference in nutrient can be found based on the land use instead of the bedrocks. Usually cropland and even grassland is fertilized. So, I would expect to find lower nutrients mainly in woodland. You have the data for the parent material and the land use – prove it, instead of referring to some references Line 341-343: Also in the croplands, I would highly doubt that and you have date to prove it – do it! Line 344: The authors should precisely use and explain which parameters they assume to influence EPS stabilization and then use them all accordingly, not once including more (Line 340), next time less (Line 344) Line 345-346: Prove it! Is a low pH going along with reduced microbial parameters lower MBC, lower CUE, ….. Line 346-349: The authors did not prove the first step in my point of view, that the bedrock is making the difference in soil properties (not differences in bedrock chemistry – please be precise) – I can find that data. The authors found significant different EPS concentrations, the rest is speculation…. Revise it accordingly Line 462-463: The authors found a weak negative correlation line 261- 262 – so is it worse pushing it here – or would be better to try to discuss instead of refreshing what others propagated but have been seldom proven. Line 467-468: refer to the data – where can I find it as a reader – such a figure with this correlation would be nice to see in the supplement! Line 331-333: What do the authors mean by “promote adsorption”? I thought the EPS is bound via Ca-bridging!? Clarify Line 33-335: How did the authors study sorption and stabilization controls on EPS concentrations (maybe I missed that point?) – it can´t be evident from a correlation!!!! Refer to the data that all these properties are highest in the carbonate soils – I would wish to prove that. Line 337: The authors should better let us participate in their nebulous explanations, what is meant here by “positive feedback mechanisms”. Line 350-364: Condense and stick to the data you have. 366-368: Please prove it and how does that fit with the discussion beforehand? Did you have cropland on silicate bedrock!? Line 368-370: Do you prove if the lowest plant root input in cropland caused the lowest MBC levels!? I always thought it is due to the overall management (mechanical and chemical interventions)! Maybe the croplands are just lowest in EPS stabilization properties? Just sarcastic joke… please revise your discussion along your data and what you can prove and not prove. Instead of interpreting your data once like that and then the other way around as it better suits your story. Line 373-374: How is agricultural management reducing stabilization properties? And if you find overall lower MBC, how will the management increase EPS degradation? Line 382-385: Which difference reflects what! Explain! Line 386: How can the authors come up with an EPS accumulation!? You did not study that, or? Line 388-393: here the authors open up another discussion box – which they also can´t prove – delete – unnecessary for the study Line 398-400: It would help if the authors include a precise description of the calculation. Line 401: Prove that number! Line 401-404: But microbes produce a variety of EPS sugars and proteins – even single microbes can produce different EPS constituents – how does that relate to your estimation based on one species!? Line 404: Still unclear how you then come up with EPS-C (summing up!?)? Line 413: what is meant by highly active soil C pool? How can a highly active C pool promote SOC stabilization – seem contradicting to me? Line 415-416: “amplifying effect on the soil C cycle”? – please stick to your data! Line 416-419: Sorry, I can´t follow this line – I can´t find a prove of this statement within this manuscript! Line 419- 420: Coming up with such statement after demonstrating such a low contribution to SOC is really confusing! Line 421-440: Why is this part of the discussion here – separate section – if the authors want to point out that necromass is important! Line 421-446: Stick to your data and not conclude assumptions! Rewrite and condense Line 477-478: Why do the authors think so? If EPS is a kind of survival strategy C would rather allocate into EPS, then growth, or? How do the authors come up with their assumption – based on what? Line 484-485 and Line 492: Prove that – refer to data and how do the authors interprete the positive correlation between MBC and EPS, the higher the microbial biomass the higher EPS – as shown by your data – how is that fitting to your argumentation? Material and Methods: 4.2. Sampling: Line 544-546: It is still unclear how many samples per site are analyzed. What forms the replicates? How where the cluster build, based on which assumptions? It is not enough to give citation in regard to its importance. Line550: Which data have been taken within these study and which data come from other studies? Needs clarification. Line 543-544: The authors need to clarify when the analyzes were done (sampling in 2017) and if the storage of the soil samples can change EPS concentrations. Microbial parameters are variable depending on the soil storage. Please clarify! How comparable are EPS extraction from dry and wet soil samples? For dry samples usually provide higher SOC extracted due to the dead organisms – don´t you extract completely different substances? Line 592-596: I shortly checked the method by Redmile-Gordon and the amount of CER added to fresh soil is depending on the SOC content. Is it correct that the authors haven´t done that!? Line622-626: The estimation of EPS-C is a central part of the manuscript. The authors need to give more informations on how the EPS-C estimation (calculation) has been done instead of referring to a reference. It is necessary to a reader to be able to follow and understand the manuscript.", "reviewer_5": "[Comment 1] The manuscript by Ke Shi and co-workers explores spatial variations in extracellular polymeric substances (EPS) across Europe. This is a timely topic, as EPS plays important roles in modulating microbial activity in soils, with potential consequences for carbon and nutrient cycling. EPS spatial patterns and their drivers are largely unknown, so this is a welcome contribution. I should add that my background is in engineering (and modelling) and I don’t feel I can evaluate the methodology developed for EPS analysis. Therefore, my review focuses on conceptual aspects and data analysis. Overall, this is a well-written manuscript (though I would suggest some changes especially in the Discussion—see detailed comments below), with a clear structure and neatly-presented results. I like the progression from simple soil groupings (by land use or geology) to more detailed analyses of EPS dependence on various climatic, soil, and biological predictors. Nevertheless, I have some (relatively minor) comments on the interpretation the results. [Response 1] We sincerely thank you for the thoughtful and constructive comments, and for recognizing the value and timeliness of our study on the distributions of soil EPS across Europe. We truly appreciate your positive feedback. In response to your insightful suggestions, we have carefully revised the manuscript and provided detailed point-by-point responses below. [Comment 2] EPS production efficiency is defined as the ratio of EPS carbon (EPS-C) to microbial biomass carbon (MB-C). In my view, this is not a production efficiency, which would be rather defined as a rate of EPS production per unit microbial growth (or carbon uptake). My impression is that calling the EPS-C/MB-C ratio ‘production efficiency’ can be misleading. Indeed, some of the interpretations of this ratio in the Discussion mix up aspects related to EPS production and decay, which I agree are both important. I suggest to change the terminology to ‘biomass specific EPS’ or something along those lines. For example, in L276-277 it is stated that ‘EPS production efficiency promotes EPS accumulation’, but the data only indicate that EPS and EPS per unit biomass are correlated, suggesting that microbial biomass does not affect much the variation in EPS (if I interpret correctly). I agree with the statement in L322, which points to EPS as result of production and decay. But then the following statements introduce some confusion by interpreting production efficiency as the result of production and decay—I would clarify this part of the Discussion. [Response 2] Thank you very much for your thoughtful and important comments. We fully agree that the EPS-C/MBC ratio does not represent true “production efficiency” in a physiological sense, as it does not account for rates of EPS formation relative to microbial growth or carbon uptake, nor does it separate EPS production from degradation processes. Following your suggestion and those of Reviewer 1 (see also our responses to Reviewer 1’s comment 4, R1-4, and comment 16, R1-16; the same applies below), we have replaced the term “EPS production efficiency” throughout the manuscript with “EPS-C/MBC ratio” to avoid misinterpretation. We also revised the relevant parts of the Introduction and Discussion Section to clarify that this ratio reflects the relation between microbial extracellular / non-growth carbon (EPS) and microbial (cellular) biomass carbon (MBC) at steady state, both underlying concurrent formation and decomposition (turnover) processes, and therefore the relative allocation of microbial biomass C to EPS at any given time point. At the same time, we acknowledge that the observed EPS levels are the net result of production, degradation, and potential stabilization in the soil; this is detailed in the main text on Pages 5 (Lines 84-93; all page and line numbers refer to the revised clean version without track changes), 10 (Lines 283-287) and 12 (Lines 358-362), and also addressed in our response to R1-1 and R1-11. Moreover, we removed or rephrased previous statements that implied causal relationships between the ratio and EPS accumulation. [Comment 3] I struggle to reconcile the function of EPS and the activity of extracellular enzymes. Are extracellular enzymes targeting EPS? This is a general comment, and not meant to criticize this work—still, here both enzymatic activity and EPS are measured, raising the question as to how the two interact in this dataset. The activity of some enzymes appears to be positively correlated with EPS contents, suggesting that microbes produce both and that enzymes do not affect negatively EPS (or the negative interaction is less strong than the coordinated production). Would it be worth discussing these interactions? [Response 3] Thank you very much for this insightful comment. Proteins are an integral part of EPS, the extracellular proteins (exoproteins, exopeptides) serving structural roles as well as mediating enzymatic functions. This has for instance been shown using meta-proteomics analysis of environmental biofilms such as in activated sludge flocs 33, 34, though not yet for soils. Since a part of the EPS proteins and EPS polysaccharides are not fully stabilized, they have also been considered a transient extracellular storage pool of C and N where microbial exoenzymes are secreted for their mobilization under C and/or N limiting conditions. We therefore agree that the relationship between EPS and extracellular enzyme activity is complex and deserves attention. However, in our study, we observed slight positive correlations between EPS contents and enzyme activities such as β-glucosidase (BG) and exoglucanase-cellobiosidase (CEL) (Fig. 2c). Moreover, carbonate soils exhibited the highest EPS contents as well as the highest BG and CEL activities (Supplementary Table 5), which may suggest a potential link between EPS production and enzyme secretion. Although this pattern is in line with previous findings showing that both EPS and enzymes can be co-expressed as part of microbial responses to environmental conditions, especially under nutrient-limited or stressful environments35, our results do not provide strong evidence for a causal relationship. To address this, we have now added the following statement to the Discussion Section: “EPS may also influence soil C cycling indirectly by enhancing the stability of extracellular enzymes and modulating their activity35, consistent with the weak positive correlations observed with BG and CEL” (Page 11, Lines 326-328). We hope this addition better explains the observed pattern. See also EPS-exoenzyme relations in responses R1-13, R3-16, and R4-69. [Comment 4] Statistical analyses: even random forest approaches handle well collinearity, some of the variables included are very strongly correlated, so I wonder results would be more robust or easier to explain by selecting variables a bit more before running the random forest model and evaluating the importance rankings. Moreover, it is not clear how PC1 and PC2 were combined (L658-660). [Response 4] Thank you for your critical comment. Although random forest models are relatively robust to multicollinearity, we agree that reducing collinearity among predictors can improve interpretability and model robustness. In our original analysis, we included aridity index (ADI), fine root biomass (FRB), C/N ratio of root (Root C/N), microbial biomass nitrogen (MBN), microbial growth (C ), microbial growth growth normalized to microbial biomass carbon (q ), enzyme vector length (VectorL), soil Growth pH, soil C/N, β-glucosidase (BG), soil bacteria to fungi ratio (B/F ratio), clay content, exchangeable Ca2+ (Ca ), Fe oxyhydroxides extracted with Na-dithionite (Fe ), and soil e d organic carbon (SOC). While the variance inflation factor (VIF) values were all below 10, we identified some variables with high pairwise correlations (e.g., pH with Ca , r > e 0.7; q with C , r > 0.6). Based on this, we removed pH and C . In addition, Growth growth growth due to further optimization of the dataset, Fe no longer emerged as an important driver d and was therefore excluded. At the same time, we found that exoglucanase- cellobiosidase (CEL) showed slight positive relationships with both EPS proteins and EPS polysaccharides (Fig. 2c), and thus included CEL as an additional predictor. We then re-ran the random forest model using a more refined set of predictors, including: • Climatic factor: ADI • Plant factors: FRB (biomass), Root C/N (nutrient content) • Soil nutrients: SOC, Ca , Soil C/N e • Soil texture: Clay • Microbial factors: MBN, q , BG, B:F ratio, CEL, VectorL Growth All predictors in this refined model showed VIF values = 7.76, indicating that multicollinearity was not a concern. The results of this optimized random forest model are now presented as the new Fig. 4, which replaces the original version. Original Fig. 4: New Fig. 4: Figure 4. Environmental and microbial drivers of EPS polysaccharides and EPS proteins. a Principal component analysis (PCA) of environmental and microbial variables associated with EPS polysaccharides and EPS proteins. The first and second principal components (PC1 and PC2) explain 32% and 20% of the total variance, respectively. b Importance ranking of predictors for EPS polysaccharides based on random forest analysis. c Importance ranking of predictors for EPS proteins based on random forest analysis. * p < 0.05, ** p < 0.01, *** p < 0.001. EPS, extracellular polymeric substances; ADI, aridity index; FRB, fine root biomass; BG, β-glucosidase; VectorL, enzyme vector length; B:F, bacteria to fungi ratio; Ca , exchangeable Ca2+; e WHC, water holding capacity; q , microbial growth normalized to microbial Growth biomass carbon; SOC, soil organic carbon; TP, total phosphorus; CEL, exoglucanase- cellobiosidase; MBC, microbial biomass carbon; MBN, microbial biomass nitrogen. Moreover，we agree that the method for combining PC1 and PC2 in constructing the soil and microbial composite variables should be described more clearly. In the revised analysis, we simplified the approach by using only the first principal component (PC1) to represent soil and microbial variables, rather than combining PC1 and PC2. This decision was based on the fact that PC1 alone captured the majority of the variance (51.25% for soil, 62.48% for microbes) and yielded well-fitting SEM models (p = 0.433; see Fig. 8a and Supplementary Fig. 1). We have revised the original sentence from “Among them, SOC, soil clay content, soil C/N ratio, Ca , and Fe were combined into a soil composite variable, while MBN, e d Cgrowth, gGrowth, and CUE were combined into a microbial composite variable using PCA. Instead of using only the first principal component (PC1) or the second principal component (PC2) alone, soil and microbial variables were constructed by combining the PC1 and PC2 based on their explained variance, and this was necessary because SEM models using only PC1 or PC2 did not yield satisfactory results (p < 0.05) (Supplementary Fig. S6)” to “Among them, SOC, soil clay content, soil C:N, and Ca e were combined into a soil composite variable, while MBN, C , q , and CUE growth Growth were combined into a microbial composite variable, for both using PCA. We used the first principal component (PC1) to represent each composite variable, as it captured a substantial proportion of the variance (51.3% for soil, 62.5% for microbes) (Supplementary Fig. 1)” (Page 19, Lines 601-605). This simplified approach provided a more transparent representation of the underlying variation compared with the previous weighted combination of PC1 and PC2. [Comment 5] Data availability: it would be useful to be able to access the data in an open access repository. [Response 5] Thank you for your suggestion. We have now uploaded the EPS-related variables (including EPS polysaccharides, EPS proteins, total EPS, EPS-carbon, and site information such as bedrock type, land use type, latitude, longitude, and elevation) as Supplementary Dataset 1, and the data we compiled from previously published studies on soil EPS as Supplementary Dataset 2. Other related datasets (e.g., microbial necromass carbon, microbial carbon use efficiency, and additional microbial variables) are not yet published and therefore are not included at this stage; however, their mean values across different bedrock and land-use types are provided in Supplementary Table 5. [Comment 6] General: EPS is expressed as carbon mass per unit mass of soil, so I would call it ‘content’ (mass/mass ratio) rather than ‘concentration’ (mass/volume ratio) (McNaught, A.D., Wilkinson, A., 1997. IUPAC Compendium of Chemical Terminology, Blackwell Scientific Publications). I realize the terminology in the literature is inconsistent to this regard, so I do not feel strongly in either direction. [Response 6] Thank you for the important comment and for pointing us to the IUPAC terminology. We agree that “content” is more accurate in this context (mass of carbon per mass of soil), and therefore have replaced “concentration” with “content” throughout the manuscript where applicable. [Comment 7] Section 2.1: please define acronyms in the Results section, otherwise it is hard to read the text while continuously flipping pages to get to the definitions in the Methods. [Response 7] We agree that defining acronyms upon first use in the Results section improves readability. Accordingly, we have ensured that each variable is introduced with its full name at first mention, followed by the acronym in parentheses throughout the Results section. [Comment 8] Figure 2: this figure is very dense of information, so I wonder if it could be simplified e.g., by removing the correlation heatmap for the ratio of EPS polysaccharide to EPS protein. I might have missed the importance of this ratio (I think it is only briefly mentioned in the Discussion), and in any case it does not seem to be highly correlated with many drivers. [Response 8] We have revised Fig. 2 to improve clarity by moving the correlation heatmap for the ratio of EPS proteins to EPS polysaccharides to Supplementary Fig. 5. As this ratio was only briefly mentioned in the Discussion and showed limited correlation with most drivers, we agree that its exclusion helps simplify the figure and better highlight the key findings. New Fig. 2: Figure 2. Soil EPS contents and their correlations with environmental and microbial factors. a Box plots of total EPS contents (sum of EPS polysaccharides and EPS proteins) in soils from different bedrock types. b Box plots of total EPS contents in soils from different land use types. Individual data points are displayed as black dots with jitter to show distribution. Boxes show the median (middle line), 25th and 75th percentiles (interquartile range), and whiskers represent the 5th and 95th percentiles. The orange diamond in each box represents the mean value. Significant differences between groups are indicated on the plot. * p < 0.05, ** p < 0.01, *** p < 0.001, NS p > 0.05. c Heatmap showing the correlations between total EPS, EPS polysaccharides, and EPS proteins with environmental and microbial variables. Only significant correlations (p < 0.05) are shown, except for pH, which is displayed regardless of significance. Numbers in the heatmap represent correlation coefficients (r); variables without numbers are non-significant (p > 0.05). The color intensity indicates the strength of correlation, with blue representing positive correlations and orange representing negative correlations. EPS, extracellular polymeric substances; EPS PS, EPS polysaccharides; EPS PN, EPS proteins; ADI, aridity index; MAP, mean annual precipitation; PET, potential evapotranspiration; FRB, fine root biomass; WHC, water holding capacity; SMC, soil moisture content; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus; CEC, cation exchange capacity; Ca , e exchangeable Ca2+; Mg , exchangeable Mg2+; NH +, ammonium; NO -, nitrate; TDN, total e 4 3 dissolved nitrogen; TOP, total organic phosphorus; MBC, microbial biomass carbon; MBN, microbial biomass nitrogen; MBP, microbial biomass phosphorus; CUE, microbial carbon use efficiency; q , microbial growth normalized to microbial biomass carbon; MBT, microbial Growth biomass turnover time; BG, β-glucosidase; CEL, exoglucanase-cellobiosidase; VectorL, enzyme vector length; GPB, gram-positive bacteria PLFA biomass; GNB, gram-negative bacteria PLFA biomass; Bacteria, bacterial PLFA biomass. New Supplementary Fig. 5: Supplementary Figure 5 | Soil EPS proteins to EPS polysaccharides (EPS PN:PS) ratio and their correlations with environmental and microbial factors. a Box plots of EPS PN:PS ratio in soils from different bedrock types. b Box plots of EPS PN:PS ratio in soils from different land use types. Individual data points are displayed as black dots with jitter to show distribution. Boxes show the median (middle line), 25th and 75th percentiles (interquartile range), and whiskers represent the 5th and 95th percentiles. The orange diamond in each box represents the mean value. Significant differences between groups are indicated on the plot. * p < 0.05, ** p < 0.01, *** p < 0.001, NS p > 0.05. c Heatmap showing the correlations between EPS PN:PS ratio with environmental and microbial variables. Only significant correlations (p < 0.05) are shown, except for pH, leucine aminopeptidase (LAP), and bacterial to fungal ratio (B:F), which are displayed regardless of significance. Numbers in the heatmap represent correlation coefficients (r); variables without numbers are non-significant (p > 0.05). The color intensity indicates the strength of correlation, with blue representing positive correlations and orange representing negative correlations. EPS, extracellular polymeric substances; Root C, root carbon content; SOC, soil organic carbon; CEC, cation exchange capacity; NUE, microbial nitrogen use efficiency; NAG, N-acetyl-β-glucosaminidase; VectorA, enzyme vector angle. [Comment 9] Figure 8: ‘bedrock’ text is not visible (black on black). [Response 9] Fig. 8 has been revised to improve clarity — the color of the pattern representing “bedrock” has been adjusted to ensure better visibility. Original Fig. 8: New Fig. 8: Figure 8. Effects of environmental and microbial factors on soil EPS-C and EPS- C/MBC ratio. a SEM illustrating the direct and indirect pathways by which bedrock type, land use, and climate influence EPS-C and EPS-C/MBC via plant, soil, and microbial factors. Black lines indicate positive effects, and red lines indicate negative effects. Solid lines represent statistically significant paths, and dashed lines indicate non-significant paths. Significance levels are indicated as: * p < 0.05, ** p < 0.01, *** p < 0.001. Numbers on the paths are standardized regression coefficients. b Bar chart showing the loadings of four soil variables on the soil composite factor (PC1) derived from PCA. SOC, soil organic carbon; C:N, soil carbon to nitrogen ratio; Ca , e exchangeable Ca2+. c Bar chart showing the loadings of four microbial variables on the microbial composite factor (PC1) derived from PCA. MBN, microbial biomass nitrogen; CUE, microbial carbon use efficiency; C , microbial growth; q , growth Growth microbial growth normalized to microbial biomass carbon. EPS, extracellular polymeric substances; EPS-C, extracellular polymeric substance carbon; ADI, aridity index; MBC, microbial biomass carbon. [Comment 10] L211 and L417: where is the evidence of the strong association between WHC and EPS shown? WHC does not appear among the highly ranked drivers. [Response 10] We apologize for the confusion. In the original version of the manuscript, the relationship between EPS and soil water holding capacity (WHC) was only presented in the Supplementary Information, which made it difficult to support the relevant statements in the main text. To address this, we have now included them in the heatmap of Fig. 2c. Moreover, PCA revealed a strong positive correlation between WHC and both EPS polysaccharides and EPS proteins (Fig. 4a). However, WHC was not included in the random forest analysis because the model is designed to identify drivers rather than outcomes of EPS. Since WHC itself is largely influenced by EPS, it should not be treated as a predictor. Accordingly, WHC did not appear among the top- ranked predictors in the random forest results (Fig. 4b, 4c). Given the potential importance of EPS for soil water retention, we additionally included Fig. 9 to show the significant linear relationships between soil WHC, soil moisture content (SMC), and EPS, which further support the Discussion. To avoid overstatement, we have revised the sentence from “At the same time, both EPS compounds were strongly positively related to soil water holding capacity (particularly EPS polysaccharides), indicating that EPS promotes soil water holding capacity more than bulk SOC or texture do (Fig. 4)” to “Both EPS compounds were strongly related to soil WHC (Fig. 4a)” (Page 8, Lines 188-189) and the sentence in Discussion section from “One important functional aspect of EPS was shown here to be the key positive driver of soil water holding capacity, compared to weaker associations to SOC or soil texture (in the absence of direct measurements of soil porosity and pore size distribution)” to “A key functional role was evident in the strong positive association between EPS and soil water holding capacity (Fig. 9a), highlighting its contribution to soil moisture retention” (Page 11, Lines 328- 330). See also our responses R4-53. Figure 9. Linear regressions between EPS and soil water properties. a Relationship between EPS and water holding capacity. b Relationship between EPS and soil moisture content. Blue lines indicate linear regression fits with 95% confidence intervals (shaded). The R2 and p-value for each regression are shown on each panel. Each point represents an individual soil sample. EPS, extracellular polymeric substances. [Comment 11] L319: was the methodology to estimate EPS in previous papers the same as used here? Can different measurement approaches explain the differences? [Response 11] The studies we compiled for comparison all used the cation exchange resin (CER) method to extract EPS from soils following the soil CER protocol published by Redmile-Gordon et al. 36, ensuring consistency in the core extraction approach. However, it is true that almost all of these studies used fresh (moist) soils, whereas our study employed air-dried soils. This difference in sample preparation may contribute to methodological variation. To further address this, we reviewed the literature and found that Zhang et al. 37 reported lower EPS yields from air-dried soils after rewetting and 2-week pre-incubation compared to moist soils. Additionally, we conducted a small experiment to directly compare EPS extraction from dry and moist soil samples. We found that for EPS polysaccharides, extraction from air-dried soils showed a mean difference of -1% ± 3% (mean ± SE, n = 7; range: -10% to +11%) relative to fresh soils. In contrast, EPS protein extraction from air-dried soils showed a mean difference of +9% ± 1% (mean ± SE, n = 5; range: +7% to +14%) across cropland, grassland, and forest soils (Supplementary Table 3). See also our response R4-3 and R4-78 for more detail. In response, we have revised the sentence from “This difference may be due to variations in geographical area, soil management practices, microbial communities, climate, and soil organic matter content” to “This difference partly reflects differences in bedrock and land-use composition, sampling season, and methodological factors (Supplementary Discussion 1). Due to sample availability, we used air-dried soils, whereas most previous studies used fresh soils. Our preliminary experiment showed minor effects of air-drying: EPS polysaccharides decreased by 1 ± 3%, EPS proteins increased by 9 ± 1%, and total EPS (polysaccharides + proteins) increased by 4 ± 3%. Long-term soil storage had similarly no impact on EPS content (Supplementary Discussion 2)” (Page 9, Lines 253-258). To provide additional context and a more comprehensive interpretation of our findings, we have included more detailed discussions in Supplementary Discussions 1 and 2 (please see below). Supplementary Discussion 1 - Comparison with published EPS datasets To compare our EPS data with previously published values, we compiled 216 EPS data points from 22 studies using the CER extraction method, with all data available in Supplementary Dataset 2. After screening for surface bulk soils and excluding data with added substrates, 83 data points from 18 studies were retained. Across ~30 sites differing in climate, geology, and land use, previously reported mean values were 429 µg g-1 for total EPS (sum of EPS polysaccharides and EPS proteins), 335 µg g-1 for EPS polysaccharides, and 131 µg g-1 for EPS proteins (Supplementary Table 1), which were generally lower than the levels observed in our study2, 4, 9, 27, 28, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50. The higher EPS contents in our dataset likely reflect a combination of ecological and methodological factors. Ecologically, our study included a higher proportion of grassland sites (27/92 vs. 7/46 in previous studies) and calcareous bedrock (27/92 vs. 2/46), both associated with higher EPS contents. In addition, ~67% of previously published data were sampled in January–April and October, whereas our samples were collected from May to August, when microbial activity is elevated, potentially enhancing EPS production. Methodologically, soil storage conditions may influence the amount of extractable EPS. Together, these factors likely account for the elevated mean and median EPS levels observed in our study compared to the literature. Supplementary Discussion 2 - Effects of soil drying and long-term storage on EPS Due to sample availability, we used air-dried soils, whereas most previous studies used fresh soils. Zhang et al.37 reported that EPS contents of air-dried remoistened soils typically differed by -13% to +26% from those of fresh soils, depending on EPS composition, which may contribute to minor differences in absolute values. In our additional experiment comparing seven forest, cropland, and grassland soils, air-drying caused only minor changes: EPS polysaccharides decreased by 1% ± 3%, EPS proteins increased by 9% ± 1%, and total EPS (sum of EPS polysaccharides and EPS proteins) changed by 4% ± 3% (Supplementary Table 3). EPS was not measured when the original samples were collected (2017); the soils were air-dried and stored, and EPS was later determined in 2024. As a result, direct assessment of long-term storage effects on these soils was not possible. To evaluate potential storage impacts on EPS, we conducted a comparison experiment using two forest soils collected in 2021 in China. The first soil was sampled in Dongtai City (reported previously4), and the second in Nanjing in autumn 2021 for an unpublished earthworm microcosm experiment. After four years of air-dry storage (2021 - 2025), both soils showed only minor changes in EPS contents: EPS polysaccharides increased by 4% on average, EPS proteins increased by 9%, and total EPS changed by 6% on average (Supplementary Table 4). These results indicate that long-term air-dry storage had negligible effects on EPS measurements. Moreover, necromass contamination appears to have only a minor impact on EPS quantification, as shown by limited muramic acid carryover from bacterial cellular necromass (~10%)1, while other amino sugars such as galactosamine and mannosamine were shown to be integral constituents of EPS, and glucosamine distributes between EPS and necromass, which complicates clear attribution at compound-specific levels. [Comment 12] L329: the cited article compared two soils only, so I wonder if the evidence that in soils originated from sedimentary rocks microbes are more adapted to decompose EPS is really strong and worth highlighting here in the Discussion (but admittedly I only scanned the cited article…) [Response 12] Thank you for your valuable comment. We agree that the evidence from the cited article may not be sufficient to strongly support the idea that microbes in soils derived from sedimentary rocks are more adapted to decompose EPS. Moreover, since we only measured EPS at a single time point, we are unable to assess its stability or decomposition directly. Based on your suggestion and a more in-depth analysis of our data (including two- way ANOVA assessing the effects of bedrock and land use on environmental and microbial factors, variance partitioning, and correlations between EPS and environmental parameters (Supplementary Table 5), we revised our interpretation regarding EPS differences among bedrock types. See also our response R1-22 for further detail. Accordingly, we deleted the original sentence: “Comparing the three studied bedrock types, carbonate rocks are rich in base cations such as Ca2+ and Mg2+ 16, weather rapidly 17 and have neutral soil pH (Supplementary Table S15) 18, 19”. In the revised Discussion Section, we now suggest that the lower EPS content in sedimentary rock soils may be attributed to lower microbial biomass (e.g., MBC and MBN), rather than specific microbial adaptations for EPS decomposition (Pages 9-11, Lines 259-307). [Comment 13] L368-369: alternatively, low MBC can be linked to depleted soil organic matter or degraded soil after intensive agricultural practices. [Response 13] Thank you very much for your important comment. In response, we have revised the sentence to better reflect the potential role of long-term intensive agricultural management in reducing microbial biomass carbon (MBC) through soil degradation or organic matter depletion. This change aligns more closely with our data and current understanding of soil processes under cropland management. We have revised the sentence from “However, low plant root C inputs in croplands caused the lowest MBC levels and therefore, even at the highest microbial EPS production efficiencies, the lowest EPS concentrations” to “Conversely, the lowest MBC and SOC observed in cropland soils may reflect soil degradation or organic matter depletion caused by long-term intensive management practices such as tillage, which could in turn contribute to the reduced EPS levels”. However, since the effect of land use on soil EPS was not significant (Fig. 2b), this part of the discussion has been moved to Supplementary Discussion 4. More responses on land use effects on EPS can be found in R3-13, R4-57, R4-58, and R4-59. [Comment 14] L398: rather than ‘contents’ I would call these ‘fractions’ (mass or EPS per unit mass of soil organic carbon). [Response 14] The sentence has been removed as part of the revisions to refine the discussion section. [Comment 15] L400-404: this material was reported in the Methods and does not add much to the Discussion. [Response 15] We recognize that this repetition may lead to redundancy in the manuscript. As this information has already been described in the Methods section (Pages 17-18, Lines 542-557), we have removed the following sentences from the Discussion Section: “Based on literature data and own measurements of model EPS polysaccharide compounds, we derived an average 39.1% C for EPS polysaccharides. In addition, a representative EPS protein C content was derived from genomic data, here the yeast Saccharomyces cerevisiae, to predict the amino acid compositions of all potentially expressed polypeptides, which produced a protein C content of 50.7% 51”. [Comment 16] L416: not clear what ‘amplifying effect’ means. [Response 16] Thank you for raising this important question. We acknowledge that the original expression “amplifying effect on the soil C cycle” was vague. Our intention was to highlight a possible functional role of EPS in modulating soil enzymatic activity, which may in turn influence C cycling processes. For instance, in our study, we found slight positive correlations between EPS and β-glucosidase (BG) activity, as well as with cellobiohydrolase (CEL, exoglucanase) activity (Fig. 2c). In line with this, a review by De Beeck et al. 35 discusses how fungal EPS matrices can enhance the stability and activity of extracellular enzymes under varying soil conditions (e.g., pH, temperature, and denaturing agents), potentially affecting biogeochemical processes. However, our results do not provide strong evidence for a causal relationship, and we have therefore only briefly discussed this phenomenon in the manuscript (Page 11, Lines 326-328); please see our response R3-3 for the specific revision. For further revisions and detailed discussion on enzyme–EPS interactions, please refer to our responses R1-13, R3-3, and R4-69. [Comment 17] L420: suggested change ‘climate change effects in agricultural systems’ [Response 17] We have revised the sentence to emphasize its relevance under climate change (Page 11, Line 332). [Comment 18] L426-427: please add rough time scales for decomposition of EPS and microbial necromass, as these statements are now quite vague. [Response 18] Thank you very much for your valuable suggestion. We agree that adding time scale for the turnover of EPS and microbial necromass helps to clarify the contrast between their persistence in soil. We also revisited the literature for experiments where 13C- or 14C-labeled EPS or EPS-mimics (soluble proteins or polysaccharides) or killed isotopically labelled microbial cells (as necromass-mimics) were added to soils and their decomposition tracked. Extractable microbial/plant polysaccharides and proteins as EPS-like compounds added to soils decomposed fast (60-80% lost as CO in 4-6 months) while fungal 14C-melanin (<15% loss in one year) 2 52, 53, 54 and bacterial and fungal 13C-labeled cells decomposed slowly, with mean residence times of 2-8 years 55. Clearly, such experiments are highly artificial, and decomposition of EPS and necromass formed autochthonously in soils, bound to soil particle surfaces, likely turns over more slowly than dissolved or particulate matter added allochthonous. We have now revised this sentence from “EPS is an active pool that is selectively secreted by microorganisms in response to adverse environmental conditions, being limited in quantity, but otherwise exhibits relatively rapid decomposition 6, 56. As the inevitable product of microbial turnover and death, MNC is rather recalcitrant against degradation, and by binding to soil mineral surfaces is preserved in soil for prolonged periods to become an important source of SOC 57, 58, 59” to “EPS is a transient pool that is selectively secreted by microorganisms in response to adverse environmental conditions, with no measurable legacy effects observed beyond 2.5 years28. In contrast, MNC as the inevitable product of microbial turnover and death, is more resistant to degradation, with turnover times ranging from multiple years to decades55, 60” (Page 12, Lines 343-346). [Comment 19] L463: aridity is not a measure of drought severity or frequency of occurrence; to discuss drought effects, perhaps consider a climatic index that describe the intensity and/or frequency of dry periods. [Response 19] Thank you very much for your helpful comment. We agree that aridity is not the best index for capturing the severity or frequency of drought events. Due to data limitations (i.e., we only had access to long-term mean values such as mean annual precipitation (MAP), mean annual temperature (MAT), and potential evapotranspiration (PET), we used the ADI (aridity index) to reflect long-term climatic dryness rather than short-term drought conditions. To avoid conceptual confusion, we have revised the sentence from “Although this has not yet been demonstrated for soil microbial communities, we demonstrate this adaptive phenomenon on a large scale i.e. reflected by increasing EPS production efficiency with increasing aridity (indicated by a decrease in the aridity index, ADI) and with worsening drought conditions” to “Although not previously demonstrated for soil microbial communities, we show this adaptive phenomenon at a large scale, reflected by increasing EPS-C/MBC along an aridity (ADI) gradient, suggesting microbial adaptation to long-term water-limited environments. This pattern is further supported by the negative correlation between EPS-C/MBC and SMC (Fig. 10)” (Page 12, Lines 369-372). We have also added a new Fig. 10 to illustrate the relationships between EPS-C/MBC and key driving factors. See also response R4-52 on drought and aridity impacts on EPS. Figure 10. Linear regressions between EPS-C/MBC and key soil and microbial parameters. a Relationship between EPS-C/MBC and soil moisture content. b Relationship between EPS-C/MBC and aridity index. c Relationship between EPS-C/MBC and microbial growth. d Relationship between EPS-C/MBC and microbial carbon use efficiency. Blue lines indicate linear regression fits with 95% confidence intervals (shaded). The R2 and p-value for each regression are shown on each panel. Each point represents an individual soil sample. EPS, extracellular polymeric substances; MBC, microbial biomass carbon; C microbial growth. growth, [Comment 20] L489-492: the logic here is not clear—you start by pointing to a difference between aquatic and terrestrial systems, but then you conclude that carbon and nutrient limitation promote EPS production in both. [Response 20] Thank you for pointing out the unclear logic in this sentence. We have removed the sentence “Different from aquatic systems, EPS production is obviously not stimulated as an intermittent extracellular store of C and N by secreting EPS polysaccharides and EPS proteins under ample C and nutrient supply in soils”. [Comment 21] L493-494: I did not understand how exoenzymes are related to the previous sentences on EPS. [Response 21] We acknowledge that the original sentence was logically disconnected from the preceding discussion of EPS, which may have caused confusion. To improve clarity, we have now removed the sentence “Instead, C and nutrient limitation promote EPS production in aquatic and soil microbial communities, though the mechanistic underpinning remains to be resolved in soils. In aquatic biofilms resource limitation has been called for maximizing the microbial return on investment for exoenzymes 8, 23” referring to aquatic ecosystems and extracellular enzymes. [Comment 22] L518: I agree this would be great to actually estimate EPS production rates. [Response 22] We agree that quantifying EPS production rates is crucial for understanding microbial carbon allocation and its implications for soil carbon cycling. We have now revised this sentence from “Further research should focus on understanding the dynamics of EPS formation, stabilization, and turnover using isotope tracer methods” to “Further research should focus on quantifying EPS production rates and understanding the dynamics of its formation and turnover using 13C and 15N isotope tracer techniques. Complementary to this, optimizing EPS extraction and developing compound-specific analytical techniques is essential for improving characterization of EPS dynamics” (Page 14 , Lines 410-413). [Comment 23] Supplementary information: it would be helpful to provide captions of the supplementary Excel spreadsheets after the statement: ‘Tables S3-S14 are provided as an attached Excel file’. If data is not available in an open access repository, perhaps it could be included as supplementary information. [Response 23] Thank you for your helpful suggestion. To improve clarity and better integrate the supplementary information with the relevant main text sections, we have split the original sentence “More detailed analyses of bedrock, land-use types, and environmental factors influencing EPS variables can be found in Supplementary Tables S3–S14” into three separate and context-specific sentences: (1) “Supplementary Tables 6-8 provide additional results from linear models and linear mixed-effects models assessing the influence of bedrock, land-use types, environmental, and microbial factors on total EPS” (Page 7, Lines 174-176). (2) “Supplementary Tables 9-14 provide additional results from linear models and linear mixed-effects models assessing the influence of bedrock, land-use types, environmental, and microbial factors on EPS polysaccharides and EPS proteins” (Page 8, Lines 193-196). (3) “Supplementary Tables 15-17 provide additional results from linear models and linear mixed-effects models assessing the influence of bedrock, land-use types, environmental, and microbial factors on EPS-C/MBC ratio” (Pages 8-9, Lines 224-226). In addition, we have provided a “Description of Additional Supplementary Files” document, which lists the names and main contents of all supplementary tables and datasets, to improve clarity and accessibility. The EPS-related variables—including EPS polysaccharides, EPS proteins, total EPS, EPS-carbon, and site information such as bedrock type, land use type, latitude, longitude, and elevation—are provided as Supplementary Dataset 1, while data compiled from previously published studies on soil EPS are included as Supplementary Dataset 2. Other related datasets (e.g., microbial necromass carbon, microbial carbon use efficiency, and additional microbial variables) are not yet published and therefore are not included at this stage; however, their mean values across different bedrock and land-use types are provided in Supplementary Table 5. We also added a sentence “All core data supporting the findings of this study are included in the Supplementary Information” in the Data Availability to clarify this (Page 20, Line 629). See also our response R3-5. [Comment 1] Overall, the authors tackle an interesting topic which highly discussed within the community. However, in my point of view that authors do not help in going a step further. [Response 1] We sincerely thank you for this insightful comment and for acknowledging the relevance of the topic. We understand your concern regarding the need to move the field forward. We apologize if this was not sufficiently clear in our original manuscript and would like to take this opportunity to clarify the novel aspects of our work. We believe our study advances the field in several key ways: (1) Large-scale survey: While EPS is increasingly recognized for its role in soil health and soil organic carbon (SOC) cycling, most previous studies have been limited to laboratory experiments or small-scale field surveys. Large-scale investigations, particularly across climatic and geological gradients, have been lacking. Our study represents the systematic survey of soil EPS across a European transect, covering diverse climatic and geological conditions. (2) Comprehensive assessment of drivers: Previous studies have typically focused on a narrow set of potential drivers. In contrast, we evaluated 66 climatic, vegetation, microbial, and soil variables to identify the key factors controlling EPS across the European transect. (3) Differentiation of EPS components: We explicitly explored whether EPS polysaccharides and EPS proteins follow similar or distinct environmental drivers, providing new insights into the ecological roles of different EPS fractions. (4) Quantification of EPS-C: Using conversion factors, we provided an estimate of EPS-carbon (EPS-C). While this approach does not allow precise quantification of EPS-C, it enables comparison with microbial necromass carbon (MNC) and places EPS-C into a broader soil carbon context. We have also revised the Introduction to better emphasize the research gap and questions addressed in this study (Pages 4-5, Lines 72-79; Pages 5-6, Lines 113-125; all page and line numbers refer to the revised clean version without track changes). In addition, in this revised version, we have undertaken major efforts to strengthen our contributions: (1) refined wording throughout to replace vague expressions with precise and professional terminology (e.g., replacing accumulation and contribution with EPS content, and using EPS-C/MBC ratio—cautiously proposed as a proxy for the relative allocation of microbial carbon assimilates to extracellular non-growth products under steady-state conditions—rather than “EPS production efficiency”); (2) optimized the methodological section by providing a more detailed description of the procedure used to estimate EPS-C (including conversion factors and formulas) (Pages 17-18, Lines 541-571) and by elaborating other methodological details for greater clarity and reproducibility (Pages 15-16, Lines 445-482); (3) deepened the statistical analyses by incorporating two-way ANOVA, variance partitioning analysis (VPA), and redundancy analysis (RDA) to better assess the drivers of EPS (Supplementary Table 5), and added Figs. 9 and 10 to illustrate the linear relationships of EPS and the EPS-C/MBC ratio with key factors.; (4) substantially revised the Discussion, offering an in-depth interpretation of how EPS responds to bedrock type and land use based on more comprehensive data analyses (Pages 9-11, Lines 259-307 and Supplementary Discussion 4). We hope that these improvements contribute to a deeper understanding of the underlying mechanisms driving soil EPS at large scales. We further hope these improvements help address your concerns and more clearly demonstrate the contribution our study makes beyond existing work. [Comment 2] There is no questioning of the data in relation to a mechanistic understanding. In my opinion, the authors should have an idea of possible connections, which they then test in order to really take a step towards a better understanding. Everything was related to everything, but I miss the mechanistic idea behind it and it´s explanation. It would be better if the authors state clear hypothesis and test them. [Response 2] Thank you very much for your critical comment. We have revised the Introduction to more clearly indicate the research gaps we aim to address and the key questions we seek to answer (please see our responses to Reviewer 4’s comment 22, R4-22, and comment 24, R4-24) (Pages 5-6, 113-125; 129-132). In addition, based on more comprehensive data analyses, we have revised the Discussion to better articulate mechanistic insights into how bedrock type and land use may influence EPS content and the EPS-C/MBC ratio, reducing inappropriate interpretations and strengthening the discussion with deeper analyses of these mechanisms (see our responses R1-22, R4-45, and R4-57, Pages 9-11, Lines 259-307 and Supplementary Discussion 4). [Comment 3] Furthermore, I have several doubts in terms of the methodology used. Some examples In the methodology section it is not becoming clear, which data have been taken from other studies and which data were analyzed on which kind of samples (Stored over how long!?) with which kind of purpose, several methods are just mentioned and the methodology is just referenced. But as a reader I expect to find the most important information within the paper. As the authors did EPS extractions on dry soil stored for an unknown period of time between 2017 and 2025, which I would highly question to produce the same results as other studies of EPS usually extracting EPS from fresh soil samples (could be one reason why the authors gained higher EPS concentrations!?), I am also questioning how and under which conditions the other data have been gained, e.g. CUE!? Same with the turnover time (microbial biomass turnover time) – how was determined on the sample taken along the transect and why was it related to EPS – what is the expectation behind? [Response 3] Thank you very much for your valuable and thoughtful comment. We appreciate your concern regarding the clarity and reproducibility of the methodology. In response, we have made the following clarifications and revisions: (1) Clarification of data sources and sample types: We have added these sentence “A comprehensive set of soil physicochemical, plant, and microbial parameters was used in the analyses, compiled from both previously published sources61 and unpublished datasets within the same project framework. Soil physicochemical properties were analyzed on either air-dried or fresh samples depending on the parameter. Soil texture (sand, silt, and clay), cation exchange capacity (CEC), exchangeable Ca2+ (Ca ) and Mg2+ (Mg ) were determined on air-dried soils by e e the Austrian Agency for Health and Food Safety (AGES) according to European and international standards (ÖNORM). Fe oxyhydroxides and Al oxyhydroxides were determined on air-dried soils by extraction with acid ammonium oxalate (Fe and Al ) o o and Na-dithionite extracts (Fe and Al ) at the Institute of Soil Research (IBF, d d University of Natural Resources and Life Sciences, Vienna, Austria)”(Page 15, Lines 446-454), “Roots, collected during soil sieving, were washed and oven-dried at 60 °C to determine fine root biomass (FRB). Dried root and air-dried soil samples were ground and analyzed for root carbon (C) and nitrogen (N) contents, and for soil organic carbon (SOC) and total nitrogen (TN) using an elemental analyzer. Root phosphorus (P) was determined by dry ashing, acid extraction, and colorimetric measurement, and root C:N:P ratios were subsequently calculated. Soil pH was measured in water (1:5 (w:v)) using an ISFET pH sensor (Sentron, Leek, the Netherlands). Soil total P (TP) and inorganic P (TIP) were determined from 0.5 M H SO extracts of ignited and control 2 4 samples, with reactive phosphate quantified colorimetrically using malachite green. Organic P (TOP) was calculated as TP – TIP, and soil C:N:P ratios were subsequently calculated. Dissolved organic C (DOC) and total dissolved N (TDN) were measured in 1 M KCl extracts (1:5, w:v; 1 h) after filtration through ash-free cellulose filters (Whatman) using a TOC/TN analyzer (TOC-VCPH/TNM-1, Shimadzu, Austria). Ammonium (NH +) and nitrate (NO -) were determined colorimetrically. Soil water 4 3 holding capacity (WHC) was determined by saturating 10 g of field-moist soil with deionized water and allowing it to drain through an ash-free cellulose filter in a funnel for 2.5 h. Soil moisture content (SMC) was determined gravimetrically as the mass loss upon drying fresh soil. For more details on the measurement procedures, see Noll et al.61” (Page 15, Lines 455-470), and “Microbial process data, such as microbial growth (C ) and carbon use efficiency (CUE), exoenzymes, and microbial C, N, and P were growth measured on fresh soils directly after collection. Specifically, microbial biomass carbon (MBC), nitrogen (MBN), and phosphorus (MBP) were determined via chloroform fumigation extraction62, from which the MBC:MBN:MBP ratios were calculated. Microbial nitrogen use efficiency (NUE) was calculated based on concurrent measurements of microbial growth and gross N mineralization rates63. CUE, C , growth growth normalized to microbial biomass carbon (q ), and microbial biomass Growth turnover time (MBT) were estimated from measurements of MBC, basal respiration, and 18O incorporation into dsDNA, following Zheng et al.64” (Pages 15-16, Lines 474-482) to the Method Section to offer more detailed information on the analytical procedures. Please also see R3-5 and R3-23. (2) EPS extraction method and concerns about air-dried samples and long-term storage of samples: We thank you for your critical and insightful comment regarding the use of air-dried soil for EPS extraction. We acknowledge that EPS is typically extracted from fresh soils in many previous studies, but not in all (see Zhang et al. 37 for a tabular compilation of studies including information on EPS extraction method and fresh/air-dry soil use, while Crouzet et al. 41 extracted EPS polysaccharides from dried soils after microcosm incubation). We fully agree that ensuring the extraction method does not alter the native state of EPS is paramount. In our study, soil samples were collected from a vast geographical region, making immediate processing and fresh soil extraction logistically unfeasible. Air-drying followed by standardized storage is a widely adopted practice in soil science to preserve samples and ensure compositional stability before analysis. Furthermore, air-drying facilitates the homogenization of soils, which significantly improves the reproducibility of our extraction protocol. To address concerns regarding the potential effects of long-term storage and air- drying, we conducted additional experiments comparing EPS extractions from fresh soils, air-dried soils, and soils stored for approximately four years. These experiments indicated that while absolute EPS concentrations may be slightly affected by storage conditions, the changes were minor: for air-dried soils, EPS polysaccharides decreased by -1% ± 3% (mean ± SE), EPS proteins increased by 9% ± 1%, and total EPS (sum of polysaccharides and proteins) changed by 4% ± 3%. For long-term stored soils, EPS polysaccharides increased by 4% on average, EPS proteins increased by 9%, and total EPS changed by 6% on average. Importantly, the relative patterns across samples remained consistent (see Supplementary Tables 3 and 4). Specifically, we collected a total of seven soil samples from forests, croplands, and grasslands. After collection, soils were immediately sieved through a 2 mm mesh and homogenized. Each sample was split into two subsamples: one analyzed immediately (fresh), and the other air-dried prior to analysis. For EPS polysaccharides, extraction from air-dried soils showed a mean difference of -1% ± 3% (mean ± SE, n = 7; range: -10% to +11%) relative to fresh soils. In contrast, EPS protein extraction from air-dried soils showed a mean difference of +9% ± 1% (mean ± SE, n = 5; range: +7% to +14%) relative to fresh soils across cropland, grassland, and forest soils (Please see below). Zhang et al. 37 also compared EPS contents measured in a paddy red clay soil in a fresh state, in fresh soils after 2-weeks pre-incubation, and in air-dried soils after rewetting and 2-weeks pre-incubation, showing changes (-13% to +26%) in contents of EPS protein and EPS-polysaccharides in air-dried soils, whereas the total EPS content varied by only about 2%. EPS polysaccharide EPS uronic EPS EPS Soil Soil types acid protein sum status (μg g −1 soil) Ultisol; arable Moist 122.1 ± 16.7 41.9 ± 2.6 86.6 ± 4.8 250.6 land Ultisol; arable Dried 153.7 ± 12.9 25.7 ± 5.5 75.5 ± 5.1 254.9 land Change due to drying ↑ 26% ↓ 39% ↓ 13% ↑ 2% Long-term storage (4 years; from 2021 to 2025) did not change soil EPS after four years in an air-dried state, as in two soils both EPS components increased by only 1- 10% measured relative to fresh soil (Supplementary Table 4). Please also see our responses to similar critiques in R3-11 and particularly R4-78 for added analysis of storage and drying effects on soil EPS contents. Due to logistical constraints, we were unable to perform a direct measurement of fresh soils for this specific study. However, we opted for air-drying to ensure sample stability and homogeneity across all our samples, which was critical for our large-scale comparative analysis. We have now explicitly described this in the Methods section: “Soil EPS (including polysaccharides and proteins) was extracted from air-dried soil samples in 2024 using cation exchange resin (CER)36” (Page 16, Lines 490-491) and “Furthermore, to ensure the robustness of EPS measurements from air-dried samples used in this study, we additionally tested whether soil moisture status and storage duration influenced EPS extraction. The procedures and results are presented in Supplementary Tables 3 and 4 and discussed in Supplementary Discussion 2” (Page 16, Lines 499-502) and acknowledged this limitation in the Discussion: “This difference partly reflects differences in bedrock and land-use composition, sampling season, and methodological factors (Supplementary Discussion 1). Due to sample availability, we used air-dried soils, whereas most previous studies used fresh soils. Our preliminary experiment showed minor effects of air-drying: EPS polysaccharides decreased by 1 ± 3%, EPS proteins increased by 9 ± 1%, and total EPS (polysaccharides + proteins) increased by 4 ± 3%. Long-term soil storage had similarly no impact on EPS content (Supplementary Discussion 2)” (Page 9, Lines 253-258). Due to word count limitations, additional discussions have been included in Supplementary Discussion 2. Please see below for details: Supplementary Discussion 2 - Effects of soil drying and long-term storage on EPS Due to sample availability, we used air-dried soils, whereas most previous studies used fresh soils. Zhang et al.37 reported that EPS contents of air-dried remoistened soils typically differed by -13% to +26% from those of fresh soils, depending on EPS composition, which may contribute to minor differences in absolute values. In our additional experiment comparing seven forest, cropland, and grassland soils, air-drying caused only minor changes: EPS polysaccharides decreased by 1% ± 3%, EPS proteins increased by 9% ± 1%, and total EPS (sum of EPS polysaccharides and EPS proteins) changed by 4% ± 3% (Supplementary Table 3). EPS was not measured when the original samples were collected (2017); the soils were air-dried and stored, and EPS was later determined in 2024. As a result, direct assessment of long-term storage effects on these soils was not possible. To evaluate potential storage impacts on EPS, we conducted a comparison experiment using two forest soils collected in 2021 in China. The first soil was sampled in Dongtai City (reported previously4), and the second in Nanjing in autumn 2021 for an unpublished earthworm microcosm experiment. After four years of air-dry storage (2021 - 2025), both soils showed only minor changes in EPS contents: EPS polysaccharides increased by 4% on average, EPS proteins increased by 9%, and total EPS changed by 6% on average (Supplementary Table 4). These results indicate that long-term air-dry storage had negligible effects on EPS measurements. Moreover, necromass contamination appears to have only a minor impact on EPS quantification, as shown by limited muramic acid carryover from bacterial cellular necromass (~10%)1, while other amino sugars such as galactosamine and mannosamine were shown to be integral constituents of EPS, and glucosamine distributes between EPS and necromass, which complicates clear attribution at compound-specific levels. We agree that future studies comparing both methods would be valuable to standardize the protocol. While the absolute values might be influenced by air-drying, the relative differences observed among experimental groups are considered reliable and informative for the purposes of this study. Supplementary Table 3 | Comparison of EPS extraction between fresh and air-dried soils from different land use types in China. EPS EPS Total EPS EPS Total Soil Site Land use Soil type polysaccharides proteins EPS polysaccharides proteins EPS dry/moist (µg g-1 soil) dry vs fresh Dongtai City, Jiangsu Province Forest Fluvisol (Sandy loam) dry 156.64 197.75 354.39 -7% 7% 0% Dongtai City, Jiangsu Province Forest Fluvisol (Sandy loam) fresh 168.60 184.23 352.83 Pukou District, Nanjing Cropland Yellow brown soil dry 140.10 135.88 275.98 4% 14% 9% Pukou District, Nanjing Cropland Yellow brown soil fresh 135.16 119.05 254.20 Laoshan, Nanjing Forest Calcareous soil dry 313.20 326.90 640.10 4% 9% 7% Laoshan, Nanjing Forest Calcareous soil fresh 300.11 300.23 600.35 Yunnan Province Grassland Red soil dry 62.78 NA NA -5% NA NA Yunnan Province Grassland Red soil fresh 65.89 NA NA Cixi, Zhejiang Province Cropland Coastal alluvial sediments dry 132.67 NA NA -6% NA NA Cixi, Zhejiang Province Cropland Coastal alluvial sediments fresh 140.91 NA NA Pukou District, Nanjing Forest Yellow brown soil dry 220.96 146.25 367.21 -10% 8% -4% Pukou District, Nanjing Forest Yellow brown soil fresh 245.02 136.03 381.06 Sihong County, Suqian Forest Alluvial deposits dry 355.26 293.08 648.34 11% 7% 9% Sihong County, Suqian Forest Alluvial deposits fresh 320.02 273.38 593.40 Purple Mountain Park, Nanjing Forest Humic cambisol dry 336.02 NA NA 4% NA NA Purple Mountain Park, Nanjing Forest Humic cambisol fresh 323.99 NA NA EPS, extracellular polymeric substance. Total EPS refers to the sum of EPS polysaccharides and EPS proteins. NA indicates that the data are not available. Supplementary Table 4 | Effects of long-term storage on EPS polysaccharides and EPS proteins in soils. 2025 2021 2025 vs 2021 Average Average Average Average EPS EPS Soil type EPS EPS EPS EPS EPS EPS polysaccharides proteins polysaccharides proteins polysaccharides proteins polysaccharides proteins (µg g-1 soil) (µg g-1 soil) (µg g-1 soil) (µg g-1 soil) (µg g-1 soil) (µg g-1 soil) Earthworm microcosm soil 964.87 NA 837.84 NA 828.85 NA 1.09% NA Earthworm microcosm soil 710.82 NA Fluvisol; Forest soil 122.07 44.48 Fluvisol; Forest soil 112.27 NA Fluvisol; Forest soil 101.13 38.16 107.75 37.53 99.94 34.33 7.82% 9.33% Fluvisol; Forest soil 97.63 23.00 Fluvisol; Forest soil 123.39 44.49 Fluvisol; Forest soil 90.03 NA EPS, extracellular polymeric substances. (3) Clarification on microbial parameters such as CUE and turnover time: Microbial processes such as growth, turnover, exoenzymes, microbial biomass and carbon use efficiency (CUE) were measured shortly after sample collection in 2017, all determined on fresh soil samples. Those data are part of a previous study of large-scale environmental controls of soil microbial carbon processing and CUE, which is in the process of being published by the main author (Qing Zheng, et al., unpublished). Other soil physicochemical characteristics as potential drivers of soil biogeochemistry were measured on air-dried soil samples in 2017 and 2018, such as soil pH, texture, SOC, TN, TP, exchangeable cations, CEC, and others. We have now explicitly described this in the Methods section (Pages 15-16, Lines 474-482). [Comment 4] Furthermore, important calculations such as EPS-C is not described in detail – but used as a kind of indicator for EPS stabilization or accumulation (all of the terms used vague without clear definition). Since the calculation is not clearly explained in the method section, it feels to me as if the authors interpret the concentration as one or the other, depending on their discretion - as it suits the story better. [Response 4] Thank you very much for your thoughtful comment. We acknowledge that the definition and calculation of EPS-C were not clearly described in the original submission. In response, we have now added a new subsection in the Methods Section specifically explaining how EPS-C was calculated (please see below): Estimation of EPS-C The C content of EPS polysaccharides (39.1% C) was estimated by elemental analysis in our laboratory as the average of four microbial and plant exopolysaccharide standards, including hyaluronic acid (37.5% C), xylan (40.5% C), pectin (38.3% C), and arabinogalactan (40.2% C). The C content of EPS proteins (50.7% C) was estimated from the global average protein N content (16% N), multiplied by a weighted mean C:N ratio of proteinogenic amino acids. Given that individual proteinogenic amino acids show variable C:N ratios, ranging from 1.5:1 to 9:1, and since proteins show marked deviations in their amino acid composition, we refrained from the use of a mean proteinogenic amino acid C:N ratio. Instead, we here applied a weighted mean amino acid C:N ratio calculated from the amino acid sequences of all genome-encoded polypeptides comprising the full proteome of the yeast Saccharomyces cerevisiae as an environmental microbe representative51. This gives a proteome-average of 5.03 mol C and 1.36 mol N per mol protein-derived amino acids51, a molar C:N ratio of 3.70 (5.03 / 1.36 = 3.70) and a mass- based C:N ratio of 3.17 (5.03 mol C × 12 / 1.36 mol N × 14 = 3.17). Using a global average protein N content of 16% by mass65, 66, and a weighted mass-based amino acid C:N in microbial proteins of 3.17, the corresponding protein C content can be approximated by formula (1): protein C content [%C] = 16.0 (%N)×3.17 (C:N) = 50.7% (1) These conversion factors were applied to measured EPS polysaccharide and EPS protein contents (in mg g-1 soil dw) to estimate their respective C contents. The final formula (2) for summed EPS-C is: EPS−C ( 𝑔 𝐶 𝑘𝑔!\" soil dw) = (EPS polysaccharides × 39.1%)+ (EPS proteins × 50.7%) (2) which provides an approximate estimate based on representative C content. To our knowledge, this represents an important attempt to quantify soil EPS-C contents, as such estimations were previously hindered by the lack of representative data on the C content of EPS components. In this study, we addressed this gap by determining average C content values from standard compounds representative of microbial EPS polysaccharides and by calculating protein C from proteome-averaged protein C:N ratios and published global protein N contents. While these estimates provide a useful approximation, we acknowledge that they do not fully capture the chemical diversity of EPS in soils. (Pages 17-18, Lines 541-568). Please also see our response R4-65/66/67. We also recognize that the terms \"EPS stabilization\" and \"EPS accumulation\" were previously used without sufficiently clear definitions. To address this, we have revised the manuscript to define these terms more precisely and consistently. Specifically, we now refer to \"EPS-C content\" as the measurable pool of extractable extracellular polymeric substances in the soil, which reflects the steady-state outcome of concurrent microbial production, degradation, and potential stabilization of EPS via interactions with soil minerals. We avoid interpreting EPS-C solely as an indicator of EPS \"accumulation\" and EPS-C/MBC as proxy of EPS \"production efficiency\" and instead focus on its variation and correlations with soil and environmental factors. See also our response R1-1, R1-11 and R3-2 on the same topic. These clarifications aim to improve the transparency and rigor of our interpretations. We thank you again for pointing out this important issue. [Comment 5] Overall, the authors draw conclusions that they do not prove and rely on speculation and, force and back correlation. In addition, they use words without defining them and defining their analyses and are therefore appearing very very vague. [Response 5] Thank you for your critical and constructive feedback. We acknowledge that some of our previous interpretations may have lacked sufficient clarity. In response, we have carefully revised the manuscript to ensure that all conclusions are more tightly aligned with the data and do not overreach the scope of our analyses. See also responses R1-22 and R4-45 on speculation, data grounding, hypotheses, and testing), we have carefully re-evaluated the entire discussion section and removed or revised interpretations that were not directly supported by our dataset. Overall, the revised discussion now more strictly adheres to what our data demonstrate or statistically support, avoiding broad assumptions or unproven causal explanations. We appreciate your guidance in improving the rigor and clarity of our interpretations. For the specific revisions made to the discussion section, please see our detailed responses below. In particular, we have revised the use of potentially misleading terms such as “accumulation” and “stabilization,” which imply processes that we did not directly measure. Instead, we now refer to “EPS contents” to more accurately describe the observed values. Additionally, we have clarified that the EPS-C/MBC ratio cannot be interpreted as a measure of production efficiency, since EPS levels in natural soils are influenced by the balance of production, degradation, and stabilization (R1-11, R3-2), as well as extraction limitations (R1-22). We now refer to this ratio more cautiously as a potential indicator of microbial C allocation under steady-state conditions, and we explicitly acknowledge its limitations (Page 5, Lines 84-93; Page 10, Lines 283-287; Page 12; Lines 358-362). We hope these changes improve the clarity and scientific rigor of our manuscript and appropriately address your concerns. [Comment 6] Line 24-25: EPS is part of the SOC, or? What do you want to say in regard to the “contribution”? Specifically, as you relate to it within the next sentence. [Response 6] We agree that the term “contribution” was initially too vague and could cause confusion. To clarify: EPS is a component of SOC, contributing directly as part of the soil carbon pool. In addition, EPS plays an indirect role in SOC stabilization by acting as a “glue” that promotes aggregate formation and organo-mineral associations 8, 28. Although the role of EPS in C dynamics has been proposed in previous studies, these have generally been based on limited datasets. The goal of our study is to systematically assess the levels of EPS across soils and to identify the environmental and microbial factors that govern its content at large scales. We regret that this motivation was not clearly conveyed in the original abstract. Accordingly, we have revised the sentence from “Extracellular polymeric substances (EPS) are a vital component of microbial residues which contribute to soil organic carbon (SOC)” to “Extracellular polymeric substances (EPS) are key microbial residues that contribute directly to soil organic carbon (SOC) and indirectly stabilize it by enhancing soil aggregation”. We hope this revision improves clarity and more accurately reflects the intended meaning (Page 3, Lines 25-26). [Comment 7] Line 26-27: At that point in time it is not clear to which theories you refer too. Please rewrite. What is the specific knowledge gap you want to fulfill, “contribution” to SOC storage – drivers/controls of EPS? [Response 7] We agree that the original sentence lacked clarity. To address this and combined with other reviewer’s comments (e.g., R1-2), we have revised the sentence from “However, despite various conjectures and hypotheses regarding soil EPS controls, empirical research and experimental evidence to validate these theories have remained highly limited” to the clearer and more precise: “Yet, their abundance and large-scale environmental and microbial controls remain poorly quantified”. This revision better reflects the specific knowledge gap we aim to address regarding the contents and drivers of soil EPS at large scales (Page 3, Lines 26-27). [Comment 8] Line 29: Do you think that large scale controls matter for EPS? What is meant here by large-scale controls? [Response 8] Thank you for your helpful comment and the opportunity to clarify. By “large-scale controls,” we refer to broad environmental gradients (e.g., climate, bedrock type, land use, and soil properties) that vary across continental scales and may influence soil EPS contents and dynamics. Current empirical data on soil EPS are primarily derived from local- or small-scale field studies, with data at regional to continental scales being particularly limited. Therefore, we believe investigating such large-scale drivers is critical for understanding how EPS distribution patterns and their controlling mechanisms differ across ecosystems. Accordingly, we have revised the original sentence from “In this study, we addressed this knowledge gap by conducting extensive soil sampling across Europe, encompassing diverse climates and bedrock and land use types, to systematically investigate soil EPS contents and large-scale controls” to “We addressed this gap by conducting extensive soil sampling across a European transect spanning diverse climates, bedrock types, and land uses” to more accurately reflect the spatial scope of our study (Page 3, Lines 27-29). [Comment 9] Line 42: Unclear, what the authors mean with EPS accumulation!? Include as for EPS production efficiency… I don´t think that prompted is the right verb here – rewrite [Response 9] Thank you for your critical comment. In response, we have revised this sentence from “On a large scale, soil EPS accumulation was promoted by its production efficiency and by soil factors promoting the sorption and stabilization of EPS, such as clay content, exchangeable Ca and Fe oxides” to “Across the transect, EPS increased with microbial biomass as a proxy for EPS production potential, while soil properties such as clay content and exchangeable calcium enhanced EPS retention”, to provide a clearer and more mechanistic explanation (Page 3, Lines 34-36). See also response R1-5. [Comment 10] Line 45: In my opinion the authors should not write “critical component of the soil-stable C pool” – as at least to my knowledge it is not proven that it is part of the soil-stable C pool – and the authors do not prove that either in their manuscript – rewriting necessary [Response 10] Thank you for your helpful comment. We apologize for the imprecise wording in the original sentence. It is true that CER does not extract the stable EPS fraction and that much of the EPS determined is cycling relatively fast, which has been indicated by additions of 13C- and 14C-labelled EPS components to soils. EPS is therefore not necessarily part of the stable SOC fraction but it can contribute to stabilize SOC through aggregation. See the related responses R1-22 and R3-18. We have revised the sentence from “These findings underscore the significant yet overlooked role of EPS as a critical component of the soil-stable C pool, as it influences microbial C allocation and SOC stabilization and should be further studied to better understand soil C cycling” to “Here, we show that EPS is a functionally important microbial residue, regulated by both environmental filters and microbial allocation strategies, with significant implications for soil carbon cycling and sequestration” (Page 3, Lines 36-38). [Comment 11] Line 50 “elements” - remove by components [Response 11] Done (Page 4, Line 42). [Comment 12] Line 52-53: When I came across the number of 30-60% of SOC for amino sugars, is a contribution of 1.6% as mentioned for EPS substantial? [Response 12] Thank you for your thoughtful comment. While our data indicate that EPS contributes only ~1.6% to SOC, we consider EPS a relevant and functionally important component of SOC for several reasons: (1) EPS as a microbial investment: EPS is a costly microbial product secreted in response to environmental stressors (e.g., drought and salinity). It plays critical roles in microbial survival and adaptation, especially under shifting climate conditions 5, 8. (2) Direct and indirect contributions of EPS to SOC: Beyond its direct contribution to SOC, EPS facilitates soil aggregation and organo-mineral associations 5, 8, which enhance the stabilization of other (non-EPS) organic matter. These indirect effects are likely substantial and relevant for long-term carbon storage. See response R4-6. (3) Potential underestimation of EPS: The actual EPS content in soils may be considerably higher than current values suggest, mainly due to methodological limitations 28. See response R1-31 The CER extraction method primarily targets the more labile fraction of EPS (bound by multivalent cation bridging and electrostatic binding forces), and current techniques are not yet capable of fully recovering the more persistent, potentially stabilized forms of EPS in soil 28. See also our response R1-22. Moreover, the extraction efficiency of CER is low—estimated to capture only about 1/2 to 1/20 of total soil EPS—further contributing to EPS underestimation 36, 38, 47. In contrast, estimates of microbial necromass carbon (MNC) based on amino sugar biomarkers may be inflated, since these markers are not exclusive to necromass 29. For example, galactosamine can be found in substantial concentrations in plant residues, and other non-necromass materials, even EPS itself 29. Therefore, while measures of EPS-C are understood to be underestimates, measures of MNC are known to be overestimates 30 and perhaps with a larger margin for error and variability. This means that while on face value our results suggest that MNC was the larger pool of C, true values might be more comparable in size. Therefore, even if the measured quantitative contribution of EPS to SOC appears small, both methodological constraints and functional evidence indicate that EPS plays a critical and previously overlooked role in soil carbon cycling and stabilization. We have added the following sentence in the Introduction to more specifically highlight the importance of EPS in soil, and we hope this clarifies your concern: “Independent of the presence of soil biofilms, EPS plays multifunctional roles in soil ecosystems5, 8. EPS enhances water retention, mediates nutrient storage, and supports microbial resilience under environmental stress8. Beyond favourable effects of EPS on microbial performance, EPS contributes to SOC dynamics by serving as a microbial-derived direct C input and by promoting soil aggregation and mineral-organic associations, which are critical processes for physical and chemical stabilization of SOC5, 6. Furthermore, EPS facilitates microbial attachment to soil particles, potentially enhancing the association between microbial cellular necromass and mineral surfaces following microbial death. Such interactions between EPS and other microbial residues may accelerate soil microbial-derived C stabilization and thus represent an additional, underexplored pathway through which EPS can promote long-term C storage50. These diverse functions underscore the ecological relevance of EPS in structuring soils and regulating C cycling” (Page 4, Lines 59-70). [Comment 13] Line 55: “a natural mixed polymer” – as I understood EPS composition, it is composed by a variety of different constituents – please adapt [Response 13] Thank you for your helpful comment. We have revised this sentence from “EPS is a natural mixed polymer secreted by microorganisms that supports them to resist environmental stresses and absorb nutrients and other resources 6, 23” to “EPS comprises a heterogeneous mixture of biopolymers (exoproteins, exopolysaccharides) targeted for their extracellular role and secreted by microorganisms that support them to resist environmental stresses and absorb nutrients and other resources6, 23” to improve accuracy (Page 4, Lines 48-50). [Comment 14] Line 70: I would wish that the authors elaborate a bit more on the “potential outstanding role of EPS… for SOC dynamics…” it is mentioned for the microbial functioning but for SOC dynamics it remains unclear to me at that point in time, specifically if their existence is debated overall in soil. That points need more preparation in my point of view, specifically if that is a main topic for the whole manuscript. [Response 14] Thank you for your important comment. We agree that our original framing did not sufficiently elaborate on the potential implications of EPS for SOC dynamics. While our previous version briefly mentioned that EPS may contribute to soil structure through its viscosity and water-holding properties, we recognize the need to make the relevance of EPS to SOC dynamics more explicit. While the continuous presence of biofilms in soils remains debated, the presence of EPS in soils is well established and not in question 8, 67. To address this, we have clarified that EPS may influence SOC dynamics through both direct and indirect mechanisms. Specifically, EPS contributes directly to the SOC pool as a form of microbial residue, and indirectly by promoting soil aggregation and mineral–organic associations—processes that are essential for the stabilization of SOC. Accordingly, we have revised this sentence (Page 4, Lines 59-70), please see response R4-12). [Comment 15] Line 72: In regard of the existing literature the authors should check the current literature a bit stronger – e.g. Zhang et al. 2023 Chemical geology a whole table summarizing studies of EPS measurements from different soil types, including different land uses as well. [Response 15] Thank you for your valuable suggestion. We apologize for the oversight in our previous literature coverage. We have now re-examined the literature on soil EPS using the CER extraction method and updated our database accordingly (Please see the Supplementary Dataset 2). Specifically, through a comprehensive literature review, we collected 22 studies using the CER method for soil EPS extraction, comprising 216 EPS measurements. After filtering to retain data from bulk topsoil, including some pre- incubated samples without added C or N, 18 studies with 83 measurements remained. Mean values from these datasets were calculated (Supplementary Table 1) and plotted in the revised Fig. 1. Figure 1. Comparison of EPS polysaccharides and EPS proteins across the European transect and with data derived from previous studies. a Comparison of EPS polysaccharide contents. b Comparison of EPS protein contents. Data were collected from 18 previous studies that used the cation exchange resin method to extract soil EPS, totaling 30 site × land use combinations. The numbers in the figure indicate frequency. Specific data are listed in Supplementary Table 1, and the complete dataset is provided in Supplementary Dataset 2. EPS, extracellular polymeric substances. Supplementary Table 1 | Previously published quantitative data on extracellular polymeric substances (EPS) extracted using the cation exchange resin method. EPS polysaccharides EPS proteins Total EPS Reference Land use type (µg g-1 soil) 37 Cropland 151.08 86.56 237.64 NA 614.29 117.22 731.52 45 NA 121.02 47.67 168.69 NA 115.72 12.52 128.24 Grass-Grass 346.02 213.17 559.19 Grass-Arable 339.55 194.56 534.11 Grass-Fallow 293.99 156.96 450.95 Arable-Grass 434.87 198.24 633.11 28 Arable-Arable 317.79 184.64 502.43 Arable-Fallow 374.66 175.67 550.33 Fallow-Grass 381.50 191.27 572.77 Fallow-Arable 235.55 110.67 346.22 Fallow-Fallow 286.96 126.43 413.39 Fallow 169.00 43.00 212.00 36 Grassland 401.00 163.00 564.00 NA 398.00 122.00 520.00 46 NA 239.00 42.00 281.00 NA 264.00 60.00 324.00 Grassland 1120.00 NA NA Cropland 800.00 NA NA 47 Woodland 830.00 NA NA Cropland 743.54 NA NA Woodland 252.01 52.36 304.36 Cropland 447.44 273.29 720.74 Woodland 215.99 60.00 276.00 9 Cropland 332.80 194.10 526.90 Woodland 278.31 80.18 358.49 Cropland 272.88 145.05 417.93 48 Grassland 191.33 94.90 286.23 4 Woodland 158.31 79.28 237.58 2 Grass-Arable 467.33 177.76 645.08 Grassland 456.41 NA NA 40 Cropland 262.78 NA NA Shrub land 52.19 NA NA 43 Shrub land 76.30 NA NA Shrub land 130.37 NA NA 27 Shrub land 120.79 NA NA Woodland 158.60 44.90 203.50 44 Woodland 160.30 42.30 202.60 54 Woodland 98.30 15.70 114.00 41 Cropland 367.95 NA NA Fallow 175.43 78.97 254.40 39 Cropland 260.78 133.86 394.64 49 Woodland 317.20 301.82 619.01 Cropland 471.25 205.19 676.44 50 Woodland 691.82 364.28 1056.10 EPS, extracellular polymeric substances; Total EPS refers to the sum of EPS polysaccharides and EPS proteins. NA indicates that the data are not available. In response, we have revised the sentence from “So far, only about a dozen (~10) sites differing in climate and geology have been tested globally, with limited measurements primarily focused on differences in land use 28, soil types 9, and plantation ages 4” to “So far, the climatic and geological coverage of soil EPS measurements was relatively restricted, with studies confined to smaller-scale and/or local mechanistic questions, e.g., targeting soil EPS responses to current and legacy land use28, the interaction of land use and geology9, land reclamation39, tree plantation age4, 50, agricultural management40, 41, and root-soil aggregate interactions in forests and grasslands27, 43, 44, which has hindered understanding of large-scale controls of soil EPS” (Page 4, Lines 72-77). Please also see our response R4-41. [Comment 16] Line 74-75: The authors should introduce microbial necromass in regard to the before mentioned cellular and extracellular residues. Please better pave the way why EPS could/should affect necromass - it is not becoming clear to me where the differences between the components are. [Response 16] Thank you for your constructive suggestion. In response, we have revised the beginning of the Introduction from “Soil microbial residues are essential elements of the stable carbon (C) pool, and can be classified as cellular and extracellular residues 4, 68. Cellular residues are widely quantified using amino sugars as biomarkers” to “Soil microbial residues are essential components of the soil carbon (C) pool and can be classified as cellular and extracellular residues4, 68. Cellular residues-also known as microbial necromass-mainly consist of microbial cell wall fragments and are widely quantified using amino sugars as biomarkers59” (Page 4, Lines 42-44). This revision allows us to explicitly introduce the concept of microbial necromass early in the manuscript. Additionally, we revised the sentence from “For example, the high viscosity and water retention capacity of EPS facilitate soil particle binding and aggregation and improve soil moisture and soil structure 8” to “Furthermore, EPS facilitates microbial attachment to soil particles, potentially enhancing the association between microbial cellular necromass and mineral surfaces following microbial death. Such interactions between EPS and other microbial residues may accelerate soil microbial-derived C stabilization and thus represent an additional, underexplored pathway through which EPS can promote long-term C storage50” (Page 4, Lines 65- 69)” to better clarify the potential relationship between soil EPS and microbial necromass. [Comment 17] Line 76-77: Is this statement assumed or verified by the papers referenced? I screened the article shortly and I could find a prove of it – Please be as precise as possible in your statements … throughout the manuscript and adapt accordingly. [Response 17] Thank you for your careful observation. We have revised this sentence from “The contribution of EPS to SOC depends on (i) the microbial secretion of EPS and (ii) its long-term protection by binding with soil particles 3, 4” to “The content of soil EPS may depend on (i) the microbial secretion of EPS and (ii) its association with soil particles5, 6, 7, as well as (iii) its decomposition and recycling” to more accurately reflect the current state of knowledge and the available evidence (Page 5, Lines 80-81). [Comment 18] Line 87-95: Repetitive – can be more condensed and targeted [Response 18] We have revised this sentence from “This indicates that the soil environment and C and nutrient availability are significant triggers for EPS secretion by microorganisms 8. Finally, when microorganisms reproduce and microbial communities expand, microbial cells can increase their adhesion capacities to the surfaces of soil particles by secreting EPS, which not only strengthens their attachment but also serves as an effective barrier to block invasion from competing microorganisms 9, 23. In summary, in soils microbial EPS secretion is contingent on microbial biomass synthesis (e.g., efficacy of microbial C and N use, microbial growth) and environmental stress 8, which depend on soil pH, water content, and cation exchange capacity (CEC) 56, 69 and on the supply of soil nutrients (e.g., SOC, N, and phosphorus (P)) 35, 70, but also are related to other factors such as population survival strategies 9” to “Finally, as microbial communities expand, EPS secretion enhances cell adhesion on soil particles and helps protect against microbial competition9, 23. Collectively, these findings underscore that EPS secretion is governed by microbial growth and environmental stress8- both influenced by soil properties, nutrient availability56, 69, 35, 70, and population-level survival strategies9” to be more condensed and targeted (Page 5, Lines 99-103). [Comment 19] Line 97: As indicated beforehand, there is no prove of long-term preservation of EPS in soils – please add the prove to be able to make that statement or adapt accordingly Screened shortly - Craig et al. did not include EPS measurements and the article by Chenu – no prove of preservation – assumption due was done due to the formed structures… and that needs be cleared up…. [Response 19] We acknowledge that there is currently no direct evidence supporting the long-term preservation of microbial EPS in soils. Externally added EPS sugars and proteins decompose rapidly in soils (see R3-18). However, the lack of evidence for long-term preservation of EPS is partially explained by the specific EPS extraction method (CER) used, which only extracts weakly bound EPS (sorbed via Ca2+ bridges) but not more strongly sorbed EPS, if present (see response R1-22). More stringent extraction procedures, on the other hand, co-extract more non-EPS compounds, making the quantification of EPS challenging. In response, we have revised this sentence “Conversely, soils enhance the physical protection of EPS that is secreted by microorganisms 8, 28, where mineral binding of EPS allows for its long-term preservation in the soil and contributes to the SOC pool 4 ” to “Additionally, the content of soil EPS is influenced by its interactions with soil particles, which offer protection against degradation71, potentially affecting its contribution to the SOC pool” (Page 5, Lines 104-105). [Comment 20] Line 106: The authors need to clarify for my better understanding what they mean by “accumulation” of EPS – are the authors using it simultaneously for preservation, stabilization and why do the authors think so…. EPS are from their composition relatively easy to degrade (proteins / sugars) – I would assume that EPS occurrence in soils is quite dynamic (as microbes use it as well as nutrient storage), so why an accumulation!? Terms need to be clarified. [Response 20] Thank you for your insightful comment. We agree that the term “accumulation” may be ambiguous in this context. Our intention was to quantify soil EPS levels and identify their environmental and microbial drivers. Therefore, we have revised the sentence “Various hypotheses have been put forward regarding the controls of EPS secretion and accumulation” to “Various hypotheses have been proposed to explain the environmental controls on microbial EPS secretion and soil EPS content, but most have been tested based on laboratory or small-scale field studies” (Pages 5-6, Lines 113-115). But it is important to note that “labile” compounds such as proteins and complex sugars can accumulate in soils to levels of 10% of SOC (carbohydrates) and 80% of SON (proteins) while recalcitrant compounds such as lignin almost completely decompose and disappear in mineral soils 72, 73, 74. Therefore, though EPS is likely relatively easy to degrade and most of it will show rapid turnover, a small fraction of it might “accumulate” in soils and contribute to the long-term C preservation. [Comment 21] Line 107-108: What is the relation of the reference to the sentence? – it's starting to get exhausting – the authors studied one bedrock – what do the authors want to say – and is it really the best reference? [Response 21] Thank you for your helpful comment. In response, we have revised the sentence from “Soils derived from different bedrock types offer varying levels of protection for EPS 75” to “Soils formed from different bedrocks thus may vary in their capacity to bind with EPS5” (Page 6, Lines 119-120) and have replaced the original citation with a more relevant one. This revision is also aligned with the clarification made in our response to R4-22 below. Additionally, we have thoroughly reviewed the entire manuscript to ensure that all citations are accurate and appropriately support the corresponding statements. [Comment 22] 105-111: It would be preferred if the authors stated hypotheses which they tested in their study instead of saying that there are several out there. What specific hypotheses and procedures (compared to the other studies) guided their science? – What is new? [Response 22] Thank you for your helpful comment. In this section, we originally aimed to highlight the research gap regarding the environmental controls of soil EPS. However, we agree that our specific hypotheses were not clearly articulated. To clarify, our study was guided by the hypothesis that soil EPS levels are governed by two key processes: (1) microbial EPS secretion, which is influenced by land-use-induced changes in nutrient availability and microbial activity; and (2) the short-term retention of EPS, which depends on its interactions with soil particles and minerals, governed by texture and mineralogy inherited from the bedrock. This dual-process framework distinguishes our approach from previous studies that typically focused on a single factor (e.g., land use) or limited spatial scales. To better reflect this, we have revised the paragraph as follows： “Various hypotheses have been proposed to explain the environmental controls on microbial EPS secretion and soil EPS content, but most have been tested based on laboratory or small-scale field studies. For example, Redmile-Gordon et al.28 showed that EPS acts as a transient binding agent, with protein levels higher in grasslands than in arable or fallow soils, likely reflecting land-use-driven shifts in microbial EPS secretion. However, forest soils—characterized by distinct microbial communities— were not included. Beyond microbial production, soil EPS content also depends on its interaction with soil minerals71, shaped by texture and mineralogy derived from bedrock. Soils formed from different bedrocks thus may vary in their capacity to bind with EPS5, though recently land use was shown to be the more important effector of soil EPS content than bedrock geochemistry in a tropical wet climate9. Despite increasing interest, no field study has systematically assessed the combined effects of land use and bedrock across varying climates on soil EPS. Large-scale investigations spanning forests, grasslands, and croplands on contrasting bedrock types across a large climate gradient are therefore critical to disentangle the biotic and abiotic controls on soil EPS-C pools” (Pages 5-6, Lines 113-125). This revision introduces our research aim and conceptual framework more clearly and defines the novelty of our approach in comparison with previous work. We have revised the research questions as requested. Please refer to R4-24 for the detailed changes regarding the research questions. [Comment 23] Line 113: Does that mean that the samples were stored from this study frozen? [Response 23] Thank you for raising this point. The samples used in this study were not frozen. Instead, air-dried soils were used for the EPS extractions. We have now clarified this point more explicitly in the Methods Section by stating that “Soil EPS (including polysaccharides and proteins) was extracted from air-dried soil samples in 2024 using cation exchange resin (CER)36” (Page 16, Lines 490-491). [Comment 24] Line 115-116: “What is the distribution of EPS on global scale” – this question is not well prepared in my point of view. I would assume that the EPS concentrations and compositions change with the microbes present in soil and their abundance – probably major differences on the small scale – so what would be the gain of information from a global distribution? [Response 24] We agree that EPS content and composition closely reflect microbial community structure and abundance, which vary greatly at small spatial scales. Controls of biogeochemical properties and processes are known to change with spatial scale, from the small micro-scale to the large continental scale. For example controls can shift from micro-scale (substrate availability at the pore scale, moisture and O 2 gradients across microsites, and local microbial interactions, viruses, protists) to the regional and continental scale (climate and seasonality driving temperature and moisture constraints, plant input quantity and quality changing across vegetation types, large-scale weathering and atmospheric deposition effects on nutrient availability, and evolutionary and biogeographic effects on dominant microbial taxa). Our aim in raising the question about “global” EPS distribution is to highlight the current knowledge gap on large-scale patterns and environmental drivers of soil EPS across diverse land use systems and geologies, including a wide climatic gradient. Macroclimatic effects on soil EPS have yet to be determined, and this was at the heart of our study. Given EPS’s crucial role in soil health and structure, understanding broad-scale patterns is essential to identify generalizable controls and inform ecosystem management beyond site- specific studies. In response, we have revised the Research Question 1 from “(1) What is the distribution of EPS concentration in soils on the continental scale, and what are its physicochemical and biological drivers?” to “What is the distribution of EPS content in soils along a European climate transect, and how do land use and bedrock types influence this distribution?” to explicitly focus on the combined effects of climate, land- use and bedrock on soil EPS (Page 6, Lines 129-131). [Comment 25] Line 118-119: Again I don´t get the specification on the continental scale – needs clarification! [Response 25] In response, we have revised this sentence from “What is the contribution of EPS-C to the SOC pool, and what causes potential differences at the continental scale?” to “What is the contribution of EPS-C to the SOC pool, and what causes potential differences along a European climate transect?” to more accurately reflect the spatial scope of our study (Page 6, Lines 131-132). [Comment 26] Line 136-137: What was analyzed, why and what was the result? Instead of referring that more detailed analysis can be found in the supplement…. [Response 26] The main findings of this section are already presented in Fig. 2 and described in detail in Result Section 2.1 of the main text. In addition, we conducted supplementary linear model and linear mixed-effects model analyses to further assess the effects of bedrock type, land-use type, environmental and microbial factors on EPS-related variables. To improve clarity and better integrate the supplementary information with the relevant main text sections, we have split the original sentence “More detailed analyses of bedrock, land-use types, and environmental factors influencing EPS variables can be found in Supplementary Tables S3–S14” into three separate and context-specific sentences (see also our response R3-23): (1) “Supplementary Tables 6-8 provide additional results from linear models and linear mixed-effects models assessing the influence of bedrock, land-use types, environmental, and microbial factors on total EPS” (Page 7, Lines 174-176). (2) “Supplementary Tables 9-14 provide additional results from linear models and linear mixed-effects models assessing the influence of bedrock, land-use types, environmental, and microbial factors on EPS polysaccharides and EPS proteins” (Page 8, Lines 193-196). (3) “Supplementary Tables 15-17 provide additional results from linear models and linear mixed-effects models assessing the influence of bedrock, land-use types, environmental, and microbial factors on EPS-C/MBC ratio” (Pages 8-9, Lines 224-226). In addition, we have provided a “Description of Additional Supplementary Files” document, which lists the names and main contents of all supplementary tables and datasets, to improve clarity and accessibility. [Comment 27] Line 139: What is the soil total EPS? Why did the authors include it? is it sound to just sum up sugars and proteins? Could they not overlap? Please elaborate on that! [Response 27] In this study, we used the sum of EPS polysaccharides and EPS proteins to approximate total EPS. This approach is based on findings from previous research 76, 77, which consistently demonstrate that polysaccharides and proteins are the two major components of microbial EPS, while other components, such as lipids and extracellular DNA, typically contribute only a minor fraction (usually less than 10%) 76, 77. This is also supported by Steward et al. 78 who analysed organic carbon (OC) compounds from different EPS extracts using liquid chromatography-organic carbon detection–organic nitrogen detection (LC-OCD-OND), and total protein and polysaccharide content and concluded that “protein and polysaccharides represented the two major components of EPS and, when combined, accounted for the measured DOC in extracts”. Therefore, many EPS studies including soil studies have adopted the approach of summing CER- extracted polysaccharide and protein contents to represent total EPS, such as Li et al. 79, Xu et al. 80, Xu et al. 81, and Geyik and Çeçen 82. As the reviewer rightly pointed out, some compositional overlap may exist between polysaccharides and proteins in EPS, such as in the form of glycoproteins 76, which could lead to a slight overestimation of total EPS when simply summing these two components. However, given that polysaccharides and proteins are widely recognized as the dominant constituents of microbial EPS (~90%) and that other components (e.g., DNA, lipids) typically represent a minor fraction (~10%), this summation remains a broadly accepted and practical proxy for total EPS 76, 77. The potential overestimation due to overlap is likely small and acceptable for the purpose of comparative analysis across different environments. In a thought experiment, the overestimate would depend on the contribution of proteins to total EPS, and the percentage of glycoproteins in EPS proteins. With 10% glycoproteins in the protein fraction and 50% of total EPS being proteins, we would arrive at total EPS = (45% EPS proteins + 5% EPS glycoproteins) + (50% EPS polysaccharides + 5% EPS glycoproteins) = 105%. This certainly is a gross oversimplification, also assuming for glycoproteins 1 part glycan and 1 part peptide (glycan contributes 50% of mass to glycoprotein). A quick literature survey indicates that (i) in bacterial proteomes glycoproteins are rare (<1%), but more common in the exoproteome (several %), and the glycan portion contributes ~5–15% of glycoprotein mass; (ii) fungi show greater abundance of glycoproteins (10–20% overall proteome; >50% of exoproteome), the glycan portion contributing ~10–30% of mass. The bias, therefore, strongly relates to the share of bacterial versus fungal contributions to EPS proteins in soils. Following the reviewer’s suggestion, we have added a more detailed explanation of this to the Methods Section: “Total EPS was approximated as the sum of EPS polysaccharides and EPS proteins, following previous studies78, 79. This approximation is based on the fact that EPS polysaccharides and EPS proteins are the major components of microbial EPS, together contributing approximately 90% of total EPS76, 77. This approach has been widely employed for estimating total EPS levels. However, we acknowledge that this method may slightly overestimate total EPS due to potential overlaps between components—for example, glycoproteins which would be double- counted in the protein and the polysaccharide fraction76. Despite this, the potential bias is likely small and considered acceptable for comparative purposes across sites. The core data used in this study have been provided as Supplementary Dataset 1” (Page 17, Lines 532-540). [Comment 28] Line 145: turnover time!? Turnover time of what!? Same with the figures – clear that up! [Response 28] Thank you for pointing out this ambiguity. We agree that the original phrasing of “turnover time” lacked clarity. To address this, we have revised the term throughout the manuscript to explicitly state “microbial biomass turnover time (MBT)”. In addition, we have updated Figs. 2 and 7 to use the abbreviation “MBT” instead of the generic “turnover time” and we now clearly define MBT as microbial biomass turnover time in the respective figure captions to ensure clarity for readers. MBT is not causally linked to EPS formation, decomposition, or stabilisation. Given that MBT is calculated as the inverse of microbial growth per microbial biomass (specific growth, q ), we in most instances refrain from using MBT and use q instead, which is growth growth a physiological proxy for how fast a microbial community grows and divides, and therefore to investigate potential C allocation trade-offs between EPS formation and growth, or whether in circumstances of growth limitation (stress-induced reduction in q ) EPS production may increase as a stress response (see also R1-41 and R4-3). growth [Comment 29] Line 139-147: Instead of writing that you related everything to everything – it would be good if the authors stick to what they expected and what they found. A sentence over 9 line without any information – move to methods. By the way, Ca and Mg are nutrients and not really soil minerals! [Response 29] In response to your comment, we have removed the detailed list of environmental and microbial variables from the Results Section. In addition, we have corrected the terminology: exchangeable Ca2+ (Ca ) and Mg2+ (Mg ) are now e e appropriately referred to as soil nutrients, not soil minerals. [Comment 30] Line 196-198: Might that be due to the EPS extraction method. There also different extraction method? [Response 30] Thank you for your valuable comment. Indeed, different EPS extraction methods may yield varying results, and methodological choices can influence the observed patterns. For a review table of EPS extraction methods, see Huang et al. 11, also highlighting the mechanism of EPS extraction, important features of methods, and disadvantages, including appropriate references. Given the large heterogeneity among soils derived from different bedrock and land-use types in our study, we conducted a preliminary experiment to ensure that the chosen method – the cation exchange resin (CER) extraction approach - was effective across all soil types encountered in our study, which included carbonate, sediment, and silicate soils (Supplementarty Fig. 4). The CER method has been established as the main current EPS extraction method, though it cannot quantitatively recover all soil EPS 36, 38, 47, and therefore underestimates soil EPS (see also responses R1-22). The description of the preliminary experiment is provided in Method Section: “A preliminary experiment was conducted to optimize EPS extraction using different CER:soil ratios across soils varying in bedrock type and SOC content, showing that 1 g of air-dried soil with 10 g of CER provided a good balance for determining both EPS polysaccharides and EPS proteins (Supplementary Method 1; Supplementary Fig. 4)” (Page 16, Lines 496-499): Supplementary Method 1 - Optimizing EPS extraction across bedrock and SOC gradients Before EPS quantification, a preliminary experiment was conducted to test EPS extraction efficiency with different CER:soil ratios across bedrock types, considering the expected higher exchangeable Ca2+ levels in carbonate soils and the wide range of SOC concentration variations due to the extensive sampling range. Specifically, three carbonate soil samples and three non-carbonate soil samples with high, medium, and low SOC contents were selected. For each sample, 0.5 g, 1 g, 2 g, and 3 g of air-dried soil were weighed, and then 10 g of CER was added for extraction, to demonstrate that the CER method and dosage used are suitable for different types of soil samples with varying SOC contents. This experiment showed that using 1 g of air-dried soil with 10 g of CER provided a good balance for determining soil EPS, as 3 g was more effective for polysaccharides and 0.5 g or 1 g for proteins, regardless of bedrock type or SOC level (Supplementary Fig. 4). This preliminary test helped us ensure that the CER extraction protocol used in this study was broadly applicable across diverse soil types, thereby minimizing potential methodological biases and ensuring comparability across samples. This was particularly important in this large-scale study: exchangeable Ca2+ differs by magnitudes between limestone soils and acidic silicate soils, causes EPS binding through multivalent cation bridging, and this exchangeable Ca2+ needs to be quantitatively extracted by CER to release EPS bound through this Ca2+ bridging mechanism (see R1-22). We also appreciate the reviewer’s valuable suggestion concerning the potential influence of extraction methods, particularly with respect to the observed significant responses of EPS polysaccharides to bedrock type, contrasted with their non-significant responses to land-use type. While some variability in EPS polysaccharide extraction efficiency cannot be fully excluded, the same method (CER) was uniformly applied and optimized across all samples. Notably, EPS proteins did not show similar patterns of variation with bedrock type, suggesting that the contrasting responses of EPS polysaccharides and EPS proteins to large-scale variation in environmental drivers are unlikely to be solely due to methodological bias, but rather reflect underlying environmental or microbial controls. In response, to better focus on the main objective of our study—soil EPS dynamics and their driving factors—we have moved the discussion of the differential responses of EPS polysaccharides and proteins to bedrock and land-use types to Supplementary Discussion 5. Within this section, we have included the following sentence to acknowledge methodological considerations: “Although a preliminary experiment was conducted to optimize the extraction procedure across soil types, variability in extraction efficiency cannot be fully excluded. However, since only EPS polysaccharides, but not EPS proteins, showed significant variation with bedrock type, this indicates that the contrasting patterns are unlikely to result solely from methodological bias, but rather reflect differences in environmental or microbial regulation of EPS components”. A brief statement “Moreover, distinct environmental dependencies and biosynthetic pathways of EPS polysaccharides and EPS proteins caused their contents to be differentially by bedrock and land use, respectively (Supplementary Discussion 5)” (Page 11, Lines 311-314) has been retained in the main text for clarity. [Comment 31] Line 211: The authors should be bit careful in their statements. For me it is not becoming clear how the authors come from a correlation to the guess that “indicating that EPS promotes soil water holding capacity more than bulk SOC or texture” – please revise or explain Wild guesses and interpretations belong in the discussion – move it. [Response 31] Thank you for highlighting the inaccurate expression in our original manuscript. In response, we have revised this sentence from “At the same time, both EPS compounds were strongly positively related to soil water holding capacity (particularly EPS polysaccharides), indicating that EPS promotes soil water holding capacity more than bulk SOC or texture do (Fig. 4)” to “Both EPS compounds were strongly related to soil WHC (Fig. 4a)” to improve the scientific accuracy and better reflect our observed data (Page 8, Lines 188-189). [Comment 32] Line 227-228: Unclear how this numbers have been generated! [Response 32] In our study, EPS-C values were estimated by converting the contents of EPS polysaccharides and EPS proteins into EPS-C equivalents using conversion factors. Specifically, EPS-C was calculated as the sum of the C content from both EPS polysaccharides and EPS proteins. The C content of EPS polysaccharides was estimated at 39.1%, based on the average C content determined by elemental analysis of several representative exopolysaccharide standards (hyaluronic acid: 37.5%, xylan: 40.5%, pectin: 38.3%, and arabinogalactan: 40.2%), while the C content of EPS proteins was estimated to be 50.7% based on literature values of global protein N percentages and predicted average amino acid C:N ratios across microbial proteins 51. A more detailed explanation has now been added to Method Section (Pages 17-18, Lines 541-571) (please see response R4-4). [Comment 33] Line 235-237: Could it be that the authors extracted necromass, due to the soil storage and EPS extraction from dry soil? [Response 33] Thank you for raising this important point. As only air-dried soil samples were available for this study, EPS was extracted from air-dried soils. We acknowledge that this may increase the risk of co-extracting non-EPS metabolites, such as microbial necromass. To minimize such potential interference, we used the cation exchange resin (CER) method, which has been widely validated for its low cell lysis and high selectivity in extracting microbial EPS 36, 38, 83. Furthermore, preliminary tests across soils with different bedrock types (limestone soils and non-limestone soils) and SOC levels confirmed that CER-extracted EPS reflected consistent and ecologically meaningful patterns across environmental gradients, supporting the comparability of results (Supplementary Fig. 4). Microbial necromass did not significantly co-extract with EPS in two recent studies by Rebeca Oliva Leme 1, 84. They showed a small “contamination” of CER-extracted EPS from bacterial cultures with muramic acid, demonstrating that partially decomposed peptidoglycan from bacterial cell walls (cellular necromass) does not significantly contaminate the EPS fraction (~10% of total muramic acid in bacterial culture extracted in EPS fraction; Oliva et al. 2024). However, specific amino sugars such as galactosamine and mannosamine (and to a smaller extent glucosamine) were shown to be integral parts of EPS, yet neither being confined to microbial EPS or necromass. We have now acknowledged this limitation in the revised Discussion section by revising the sentence from “This difference may be due to variations in geographical area, soil management practices, microbial communities, climate, and soil organic matter content” to “This difference partly reflects differences in bedrock and land-use composition, sampling season, and methodological factors (Supplementary Discussion 1). Due to sample availability, we used air-dried soils, whereas most previous studies used fresh soils. Our preliminary experiment showed minor effects of air-drying: EPS polysaccharides decreased by 1 ± 3%, EPS proteins increased by 9 ± 1%, and total EPS (polysaccharides + proteins) increased by 4 ± 3%. Long-term soil storage had similarly no impact on EPS content (Supplementary Discussion 2)” (Page 9, Lines 253-258). See also responses R3-11, 4-3, and 4-78 on the topic of procedural bias by air-drying. A more detailed discussion—including comparisons of dry and wet soils from the literature, our dry–wet soil experimental results, measurements from long-term stored samples, and potential necromass biases—has been added to Supplementary Discussion 2 (see response R4-3). In an ongoing work, we also hydrolysed the extracted EPS fractions from the same soil samples and analysed their neutral sugar, amino sugar and uronic acid composition (unpublished data). We could not detect muramic acid in any EPS extract across the whole transect. [Comment 34] Line 237-239: Interpretation into the discussion [Response 34] In response to your comment, we have revised this sentence from “In addition, notably strong positive correlations were observed among SOC, MBC, MNC, and EPS-C, underscoring their interconnected roles within soil C dynamics (Figs. 5, 6)” to “In addition, notably strong positive correlations were observed among SOC, MBC, MNC, and EPS-C (Fig. 6)” (Page 8, Lines 208-209). To provide a deeper interpretation, we have retained the sentence “In addition, EPS is produced by microbes as a “glue” for attachment of their cells and colonies to soil surfaces76, which, after death, cause necromass fragments to be cemented via EPS to soil minerals or organic surfaces, which has been shown microscopically85, 86. This also promotes the strong collinearity between EPS-C and MNC, MBC and SOC (Fig. 6)” in the Discussion Section (Page 12, Lines 349-353). [Comment 35] Line 267: How did the authors investigate EPS stabilization!? [Response 35] We acknowledge that the term “EPS stabilization” was not appropriately used in this context, as our study did not directly measure or investigate EPS stabilization. In response, we have revised the sentence from “To assess direct versus indirect effect pathways between environmental drivers and soil EPS-C content, and to evaluate the importance of these effects via driving EPS production efficiency or EPS stabilization, we performed SEM analysis (Fig. 8)” to “To assess direct versus indirect effect pathways between environmental and microbial drivers and both soil EPS-C content and EPS-C/MBC ratio, we performed SEM analysis” to more accurately reflect the results (Page 9, Lines 227-228). [Comment 36] Line 268-270: Sorry, I don´t get it. Ca was positively correlated with EPS and now it has a negative effect on EPS-C!? Clarify! Heatmap of EPS driving factors – for both EPS polysaccharides and proteins compared to SEM? – to me it makes no sense The authors base all of the presented data on EPS concentrations determined at one point in time. How was an EPS-C accumulation or stabilization determined? As it is not clearily [Response 36] Thank you for pointing out this issue, and we apologize for the lack of clarity in our original wording. In the SEM, we used PCA-derived composite factors to represent complex soil physicochemical variables, and Ca2+ (Ca ) was one of the e contributing variables to this composite factor (see also response R3-4 on PCA data handling). As shown in the loading plot below the SEM diagram (Original Fig. 8b), Ca2+ had a negative loading on principal component (PC1) and a near-zero positive loading on PC2. Meanwhile, this composite factor had a negative path coefficient to EPS-C (Fig. 8a). Therefore, the indirect effect of Ca2+ on EPS-C is double-negative, resulting in a net positive association, which aligns well with the direct positive correlation observed in the heatmap (Fig. 2c). Because the SEM originally included both PC1 and PC2, it was somewhat difficult to interpret. In this revision, we optimized the SEM to use only PC1. Based on the updated results, we have revised the corresponding sentence from “Soil physicochemical variables (a composite factor negatively loaded by clay, Ca , and Fe , and SOC, Supplementary Fig. S1) had a direct e d negative effect on EPS-C. This aligns with expectations, as higher clay and Ca e contribute to EPS-C accumulation and stabilization at lower PC (soil) values” to “Soil physicochemical variables were summarized as a composite factor derived from PC1 of a PCA (Fig. 8b; Supplementary Fig. 1). Specifically, PC1 (soil) was positively loaded by the soil C:N ratio and near-zero positively loaded by SOC, while clay content and Ca , had negative loadings. In the SEM, this composite soil factor showed a negative e path coefficient to EPS-C, indicating that lower scores on this PCA-derived soil factor (i.e., higher clay, and Ca ; lower soil C:N ratio) were associated with higher EPS-C e content (Fig. 8a)” (Page 9, Lines 228-234). To better explain the effects of the PCA-derived microbial composite factor on EPS- C and EPS-C/MBC, we revised the original sentence from “In contrast, the microbial composite factor (negatively loaded by CUE, Cgrowth, qGrowth, and MBN, Supplementary Fig. S1) exerted a direct positive effect on EPS production efficiency and a direct negative effect on EPS-C (Fig. 8). This is consistent with the observed trade-off between microbial growth and EPS production efficiency, as low microbial biomass and growth (at high PC (microbe) values) are associated with high EPS-C production efficiency” to “In contrast, the microbial composite factor, derived from PCA of CUE, C , q , and MBN (Fig. 8c; Supplementary Fig. 1), exerted a direct growth Growth positive effect on EPS-C/MBC ratio and a negative effect on EPS-C (Fig. 8a). In the PCA loading, C , q , and CUE had negative loadings on PC1 (microbial), while growth Growth MBN had a near-zero positive loading. Thus, the SEM paths indicate that lower values of this PCA-derived microbial factor (i.e., higher CUE, C , and q ) were growth Growth associated with lower EPS-C/MBC ratio, supporting a potential trade-off between microbial growth and EPS investment” (Page 9, Lines 234-240). Additionally, concerning the use of “EPS-C accumulation” or “stabilization”: we agree that our data are based on a single time point and do not allow direct inference of long-term EPS accumulation or stabilization. We have now removed the term “stabilization” and “accumulation” in the main text. [Comment 37] Line 270: Which kind of expectations? And what do the authors mean by lower PC (soil) values? [Response 37] Our expectation was that high contents of Ca and clay increase the e organic matter and EPS binding capacity of soils and therefore show a positive relationship with soil EPS. In response to your comment, we have revised the sentence for clarity (also in line with response R4-36) [Comment 38] Line 276-277: refer to the data [Response 38] Thank you for your careful comment on this point. Together with the related suggestion from Reviewer 1 (Response R1-18), we realized that this statement was somewhat circular and self-evident. Therefore, to avoid redundancy and improve clarity, we have removed the sentence “Moreover, EPS-C scaled positively with EPS production efficiency, showing that EPS production efficiency promotes EPS accumulation” from the revised manuscript. [Comment 39] Discussion: It would be overall better if the authors stick to their data and what they can prove or reject instead of wild interpretations and assumptions! [Response 39] We fully agree that scientific discussion should be grounded in data. In response (see also R4-2, R4-5, and R4-22 on speculation, data grounding, hypotheses, and testing), we have carefully re-evaluated the entire discussion section and removed or revised interpretations that were not directly supported by our dataset. Overall, the revised discussion now more strictly adheres to what our data demonstrate or statistically support, avoiding broad assumptions or unproven causal explanations. We appreciate your guidance in improving the rigor and clarity of our interpretations. For the specific revisions made to the discussion section, please see our detailed responses below. [Comment 40] Line 309: The author don´t do a spatial analysis, so please be precise and write that the study has been conducted along a transect (not even covering Europe, but just some parts see Map of Noll et al). Clarify! [Response 40] Thank you for this important comment. We have revised the sentence from “This study found a high spatial variability in soil EPS concentrations across the European transect (minimum 149 µg g-1 / maximum 2495 µg g-1 (16 x the minimum value); Fig. 1)” to “Across the European transect, soil EPS contents varied widely (149 – 2495 µg g-1; 16× difference; Fig. 2)” to improve accuracy and clarity (Page 9, Lines 246-247). [Comment 41] Line 315-316: See my comment above – the authors overlooked quite some studies…. [Response 41] Thank you for your important comment. We have now re-examined the literature on soil EPS using the CER extraction method and updated our database accordingly (Supplementary Table 1 and Supplementary dataset 2). In response, we have revised the sentence from “There are only a few reports of soil EPS contents based on the CER extraction methond available in the literature, which we compiled in a data synthesis effort (Supplementary Table S1). Total EPS, EPS polysaccharides, and EPS proteins levels in our study were higher than those previously reported at ~10 sites differing in climate and geology: total EPS (mean: 393 µg g⁻¹), EPS polysaccharides (mean: 266 µg g⁻¹), and EPS proteins (mean: 126 µg g⁻¹) 2, 4, 9, 28, 36, 38” to “An extensive literature survey showed lower EPS contents (~30 sites in 18 studies differing in climate, geology, and land use), with 429 µg g-1 for total EPS, 335 µg g-1 for EPS polysaccharides, and 131 µg g-1 for EPS proteins (Supplementary Table 1). This difference partly reflects differences in bedrock and land-use composition, sampling season, and methodological factors (Supplementary Discussion 1)” (Page 9, Lines 250-254) and replotted Fig. 1. Further discussion has been moved to Supplementary Discussion 1. Please see below: Supplementary Discussion 1 - Comparison with published EPS datasets To compare our EPS data with previously published values, we compiled 216 EPS data points from 22 studies using the CER extraction method, with all data available in Supplementary Dataset 2. After screening for surface bulk soils and excluding data with added substrates, 83 data points from 18 studies were retained. Across ~30 sites differing in climate, geology, and land use, previously reported mean values were 429 µg g-1 for total EPS (sum of EPS polysaccharides and EPS proteins), 335 µg g-1 for EPS polysaccharides, and 131 µg g-1 for EPS proteins (Supplementary Table 1), which were generally lower than the levels observed in our study2, 4, 9, 27, 28, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50. The higher EPS contents in our dataset likely reflect a combination of ecological and methodological factors. Ecologically, our study included a higher proportion of grassland sites (27/92 vs. 7/46 in previous studies) and calcareous bedrock (27/92 vs. 2/46), both associated with higher EPS contents. In addition, ~67% of previously published data were sampled in January–April and October, whereas our samples were collected from May to August, when microbial activity is elevated, potentially enhancing EPS production. Methodologically, soil storage conditions may influence the amount of extractable EPS. Together, these factors likely account for the elevated mean and median EPS levels observed in our study compared to the literature. Please see also response R4-15 on the literature data study. [Comment 42] Line 319-320: (a) Maybe due to differences in EPS extraction from dry/wet soil and storage and EPS polysaccharide determinations!? Please include (b) If referring to explanations of different studies (I assume that previous studies can be checked in more detail in regard to your studied soils (ADI, carbonates and SOC – for example to check if your message can be underpinned by the other studies or not, instead of referring to a bunch of potential differences without a closer look, which is not advancing our knowledge. [Response 42] Thank you very much for your valuable suggestion. (a) We reviewed the literature and found that Zhang et al. 37 conducted a comparison of EPS extractions from air-dried soils after rewetting and 2-week pre-incubation and fresh soils. Their results showed -13% to 26% difference between the two treatments, suggesting that drying may have limited effects on EPS quantification. The same, i.e., a negligible effect of air-drying and of long-term storage was confirmed by our own supplementary experiment. We collected seven soil samples from forests, croplands, and grasslands. After collection, soils were immediately sieved through a 2 mm mesh and homogenized. Each sample was split into two subsamples: one analyzed immediately (fresh), and the other air-dried prior to analysis. For EPS polysaccharides, extraction from air-dried soils showed a mean difference of -1% ± 3% (mean ± SE, n = 7; range: -10% to +11%) relative to fresh soils. In contrast, EPS protein extraction from air-dried soils showed a mean difference of +9% ± 1% (mean ± SE, n = 5; range: +7% to +14%) relative to fresh soils across cropland, grassland, and forest soils (Supplementary Table 3). In addition, to assess the effect of long-term storage, we re-analyzed EPS in two air-dried forest soils collected in China. The first was sampled in 2021 in Dongtai City and reported previously 4, and the second was collected in autumn 2021 from Nanjing for an unpublished earthworm microcosm experiment. After four years of air-dry storage at room temperature (2021–2025), both soils showed only minor changes, with EPS polysaccharides and EPS proteins increasing by 1–10% relative to fresh soils (Supplementary Table 4). These results indicate that long-term storage had negligible effects on EPS measurements. See also responses R3-11, R4-3 and R4-78 for more details on air-drying and soil storage effects on EPS. (b) Based on these new experimental results and the literature evidence, we also revisited and compared our EPS concentrations with those reported in other studies. We have revised the Discussion accordingly; for detailed modifications, please see our response R4-41, and for further discussion, refer to Supplementary Discussion 1. We also compared our results to land use effects on EPS found by Redmile-Gordon et al.28 and Kidinda et al.9. Since the effect of land use on soil EPS was not significant in our study, we have moved this discussion to Supplementary Discussion 4, where we also included comparisons with their findings, please see below: Supplementary Discussion 4 - Land use effects on soil EPS contents and EPS-C/MBC ratios Among the three land-use types, EPS contents were highest in grassland soils compared to cropland and woodland soils, although the differences did not reach statistical significance (Fig. 2b). To identify potential drivers of EPS content variation, we found that MBC was significantly affected by land use and showed a pattern consistent with EPS (Supplementary Table 5). This, together with the positive correlation between MBC and EPS (Fig. 2c), suggests that higher MBC may indicate larger microbial populations, thereby representing a greater potential for EPS production and serving as a primary control on EPS content across land-use types. In addition, land-use exerted a stronger influence on soil nutrient status (e.g., SOC, TOP, TP, Mg , and NO -) and fine root traits (FRB and Root N) than bedrock (Supplementary e 3 Table 5). Among these, SOC and TOP were significantly higher in grassland than in cropland and positively correlated with EPS, while root N was also highest in grasslands, whereas FRB peaked in woodlands but remained relatively high in grasslands. These indicators suggest that improved nutrient availability and greater plant inputs (root turnover and exudation) may enhance microbial EPS production87. This interpretation is consistent with previous findings: Redmile-Gordon et al.28 observed the highest EPS contents in grasslands, while Kidinda et al.9 reported higher EPS in fertilized croplands than in forests on nutrient- poor tropical soils. Together, these studies suggest that land-use effects on EPS are primarily mediated by plant inputs and nutrient availability. Conversely, the lowest MBC and SOC observed in cropland soils may reflect soil degradation or organic matter depletion caused by long-term intensive management practices such as tillage, which could in turn contribute to the reduced EPS levels. For instance, frequent tillage can disrupt soil structure and aggregates, thereby reducing soil organic matter content10. On the other hand, although croplands had the highest clay and exchangeable Ca2+ contents—factors potentially favouring short-term EPS retention—their EPS levels were lowest. This suggests that limited labile C availability, linked to lower SOC and FRB in croplands, may play a more decisive role in constraining microbial EPS content across the investigated soils. Substantial differences in the composition and function of soil microbial communities under different land use types88 may also cause differences in EPS formation and decomposition89. While microbial diversity was not investigated in this study, in accordance with investigations of legacy vs current management effects on EPS28, it is primarily the interplay between plant inputs and anthropogenic management that causes these differences in total EPS and EPS protein contents. Interestingly, the ranking of EPS-C/MBC did not mirror that of EPS contents, with croplands showing the highest EPS-C/MBC, followed by grasslands and woodlands (Fig. 7b). Given that both EPS and MBC were lowest in cropland soils, this highest EPS-C/MBC ratio suggests a greater microbial investment in EPS production per unit biomass. This may be a response to increased water stress in croplands, as indicated by significantly lower WHC and SMC compared to woodlands and grasslands (Supplementary Table 5). We hope these revisions provide a clearer and more informative interpretation of the variability in EPS values across studies. [Comment 43] Line 322-323: Ok, and now go a step further – what does that mean for your interpretations!? Formatting of the reference! [Response 43] Thank you for your helpful comment. This sentence — “Generally, soil EPS concentrations are governed by the dynamic balance between its generation, stabilization and decomposition (Shi et al., 2024)” — was originally included to support our interpretation of the patterns observed in our results: specifically, that EPS contents were highest in carbonate soils, whereas EPS-C/MBC was highest in sedimentary soils. We initially interpreted this as reflecting greater EPS stabilization in carbonate soils, and potentially enhanced microbial allocation (EPS production efficiency) to EPS under nutrient-rich conditions in sedimentary soils. However, based on your comment and also insights from another reviewer (see R1- 1, R1-11, and R3-2), we now recognize that this interpretation may not be appropriate. Extracted EPS may not directly reflect EPS stabilization, and EPS-C/MBC in our study is not a reliable proxy for EPS production efficiency. Therefore, we have removed the sentence and revised the corresponding interpretation to better reflect the limitations of our data. [Comment 44] Line 326-327: The authors should elaborate a bit more on their assumption. [Response 44] Thank you for your helpful comment. We have revised this sentence “This suggested that high EPS concentrations in carbonate soils may depend on their stabilization processes 14, whereas the EPS in sedimentary rocks (despite their high EPS production efficiencies) may be rapidly decomposed due to the presence of adapted microbial communities efficiently utilizing EPS 15” and rewritten the Discussion Section to clarify our reasoning (please see response R4-45 below). [Comment 45] Line 337-339: But an overall higher microbial biomass would also mean more potential EPS producers, or? The more MBC the more EPS-C see your own figure – clarify [Response 45] Thank you very much for your valuable comment. Your suggestion, along with your comment 51, inspired us to conduct a more comprehensive analysis. We performed two-way ANOVA and variance partitioning to compare the effects of bedrock and land use on environmental and microbial factors, and related these results to the correlations between EPS and environmental and microbial parameters (Supplementary Table 5). This allowed us to reassess the differences in EPS content among the three bedrock types. See also response R1-22 and R4-22 on refined statistics and on bedrock effect interpretation. Specifically, we found that bedrock type significantly influenced MBC and MBN, which showed a positive correlation with EPS content, more so than land use affected microbial biomass. Therefore, we decided to delete the original sentence “However, greater microbial activities may result in the recycling and degradation of EPS 15, thus, eventually limiting its accumulation 24”. Based on our revised interpretation, the high EPS content in carbonate soils is mainly attributed to two factors: (1) Higher microbial biomass (such as MBC), which likely reflects a greater potential for EPS production. (2) Higher soil cation exchange capacity (CEC) and elevated levels of clay content, and Ca2+ in carbonate soils, which may promote (a) short-term EPS retention and (b) improve soil conditions, thereby supporting increased microbial biomass and EPS production (feedback on (1) increasing MBC). We have updated the Discussion Section accordingly, please see below and response R1-22: “Among the three bedrock types, EPS contents were significantly higher in carbonate than in silicate and sedimentary soils. This pattern was mirrored in microbial (e.g., MBC and MBN) and soil properties (e.g., CEC, clay, and Ca ), known e to promote EPS, all of which were significantly influenced by bedrock and peaked in carbonate soils. Conversely, sand content – which was lowest in carbonate soils – was negatively correlated with EPS contents (Supplementary Table 5). Based on these findings, we propose that the highest EPS content in carbonate soils is primarily driven by two aspects: (1) an indirect pathway, where highest soil pH and CEC (particularly Ca ) e modulates the soil microenvironment in ways that stimulate microbial activity27, increase microbial biomass (e.g., MBC and MBN) and thereby causes greater overall capacity for EPS production9; and (2) soil minerals (clay) and cations (Ca ) may e contribute to the selective retention of EPS within the soil matrix through multivalent cation bridging between negatively charged sites of EPS and other polymers and minerals5, 11. However, CER-based extraction primarily isolates loosely bound or exchangeable EPS28, stabilized through reversible Ca2+ bridging and electrostatic attraction (Supplementary Discussion 3). These fractions are unlikely to represent long-term stabilization but may provide transient protection from microbial degradation, thereby promoting short-term EPS persistence28. Additionally, although our study does not directly include microbial community diversity or composition data, previous research has shown that lithology-driven geochemical processes – such as rock weathering and mineral-associated protection – can indirectly regulate the accumulation of microbial extracellular products (such as glomalin-related soil protein) via microbial functional traits12. In particular, carbonate soils have been reported to harbor higher microbial diversity12, which, given the positive relationship between diversity and EPS production13, may reflect a greater EPS secretion potential12. Moreover, the relatively higher WHC in carbonate soils – may reflect the ecological function of soil EPS in improving soil water retention5 (Fig. 9). Interestingly, while carbonate soils exhibited the highest EPS contents, their EPS-C/MBC ratios followed a different pattern, with soils on sedimentary rocks demonstrating the highest EPS- C/MBC ratios (Fig. 7a). Although this ratio does not directly reflect EPS production efficiency – since EPS contents in natural soils result from the balance of microbial production and degradation, modulated by mineral interactions and extraction limitations – it may serve as a proxy for the relative allocation of microbial C assimilates to extracellular non-growth products under steady state conditions. Notably, sedimentary soils had the lowest EPS contents, but the highest EPS-C/MBC ratios, which likely stems from reduced MBC rather than increased EPS contents. Supporting this interpretation, microbial growth-related parameters (e.g., C , MBC, and MBN) growth were consistently lowest in sedimentary soils, which also had the lowest WHC and SMC (Supplementary Table 5). Given the decrease in MBC at lower WHC and SMC (Supplementary Fig. 2), we infer that limited water availability in sedimentary soils may constrain microbial growth and shift C allocation towards EPS formation. This shift may reflect an adaptive microbial strategy to enhance survival and maintain extracellular protection under water-stressed conditions5. Although silicate soils exhibited intermediate levels of both EPS and MBC (Supplementary Table 5), they had the lowest EPS-C/MBC ratio. This suggests that microbes in silicate soils may have allocated proportionally less C toward EPS production or are less conducive for intermittent EPS retention. Three possible explanations can be proposed: (1) Environmental stress in silicate soils may be relatively mild – for example, these soils exhibited the highest SMC and WHC – whereas more severe moisture-related stress in sedimentary soils might have triggered greater EPS production; (2) the lowest levels of Ca and clay (highest sand content) in silicate soils may have provided the least e protection for EPS (Supplementary Table 5); (3) differences in microbial community composition or metabolic strategies may also contribute to the observed pattern. However, we currently lack direct evidence to confirm the third explanation. Overall, bedrock influenced EPS through (1) promoting microbial biomass and EPS secretion via bedrock-driven environmental conditions, and (2) shaping soil texture and mineralogy, which governs EPS retention and intermittently protects it from microbial degradation” (Pages 9-11, Lines 259-307). We have added descriptions of the newly incorporated statistical methods in the Statistical Analyses section: “To investigate the effects of bedrock and land use type on environmental and microbial factors, we performed two-way ANOVA for each environmental and microbial variable. Variance partitioning analysis (VPA) was then conducted to quantify the relative contributions of bedrock and land use type to the variation in these factors. Redundancy analysis (RDA) was used to test the statistical significance of the partitions identified by VPA” (Pages 18-19, Lines 590-594) [Comment 46] Line 339-341: To be able to follow your train of thoughts I would like to check the statement that the soils developed on sediment bedrock “were intermediate in properties promoting EPS stabilization” – I guess meaning low clay, low silt, Ca and Fe contents – that’s what I would like to prove it. [Response 46] Thank you for pointing this out. We have now added a supplementary Table 5 showing the values and statistical differences of environmental and microbial factors across the three bedrock types. See other response R1-22, R4-45, R4-47, R4-50 and R4-51 on refined statistics and bedrock effect interpretation. Specifically: (1) Clay content: Carbonate > Sediment > Silicate (2) Silt content: Carbonate > Sediment > Silicate (3) Ca : Carbonate > Sediment > Silicate e (4) Fe : Carbonate > Sediment > Silicate c (5) Fe : Carbonate > Sediment > Silicate d As EPS extracted using the CER method is not considered long-term stable, we agree that the previous interpretation suggesting “EPS stabilization” was not fully supported. Therefore, we have removed this sentence “In the studied soils, those deriving from sedimentary bedrock were intermediate in properties promoting EPS stabilization (e.g., clay, silt, Ca , Fe ) but had highest EPS production efficiencies, e d which may explain the second highest soil EPS concentrations”. Additionally, we acknowledge that our previous statement indicating that sedimentary soils had the “second-highest soil EPS contents” was imprecise. This was based on the visual interpretation of the median values in the boxplot (Fig. 2), where the median EPS content in sedimentary soils appeared higher than in silicate soils. However, the mean EPS content was lowest in sedimentary soils. To clarify this, we have updated the Fig. 2 to include orange dots representing the mean values for each bedrock type, and we have revised the figure legend accordingly. [Comment 47] Line 335: I would assume that the larger difference in nutrient can be found based on the land use instead of the bedrocks. Usually cropland and even grassland is fertilized. So, I would expect to find lower nutrients mainly in woodland. You have the data for the parent material and the land use – prove it, instead of referring to some references [Response 47] Following your suggestion, we conducted a two-way ANOVA to assess the effects of both bedrock type and land use on soil physicochemical and microbial parameters potentially controlling EPS contents in soils. In addition, we performed variance partitioning to determine which factor had a stronger influence on different environmental and microbial parameters. The full results have been added as Supplementary Table 5. See also responses R1-22, R4-45, and below R4-50 and R4-51 on refined statistical treatment of bedrock and land use effects and their interpretation Specifically, the bedrock type had a greater impact on microbial biomass nitrogen (MBN), microbial biomass carbon (MBC), microbial biomass phosphorus (MBP), β- glucosidase activity (BG), β-xylosidase (BX), exoglucanase-cellobiosidase (CEL), leucine aminopeptidase (LAP), N-acetyl-β-glucosaminidase (NAG), vector angles (VectorA), carbon use efficiency (CUE), nitrogen use efficiency (NUE), cation exchange capacity (CEC), exchangeable Ca2+ (Ca ), clay content, sand content, aridity e index (ADI), water holding capacity (WHC), soil moisture content (SMC), and pH. In contrast, land use strongly affected soil organic carbon (SOC), total organic phosphorus (TOP), dissolved organic carbon (DOC), total phosphorus (TP), exchangeable Mg2+ (Mg ), NO ⁻, C:N ratio, C:P ratio, N:P ratio, NH ⁺, Al oxyhydroxides extracted with e 3 4 Na-dithionite (Al ), Al oxyhydroxides extracted with acid ammonium oxalate (Al ), Fe d o oxyhydroxides extracted with acid ammonium oxalate (Fe ), root carbon and nitrogen, o fine root biomass (FRB), emzyme vector length (VectorL), root C:N and C:P, microbial growth (C ), microbial growth normalized to microbial biomass carbon (q ), growth growth bacterial, gram-negative bacteria (GNB), and gram-positive bacteria (GPB). Relatively, land use had a greater impact on soil nutrient levels than bedrock type. Therefore, we have removed the previous inaccurate statement: “Sedimentary rocks are rich in various nutrients (such as NH +) 22 that may stimulate the microbial secretion 4 of EPS. This, in turn, can stimulate microbial resource utilization efficiency and microbial activities through a positive feedback mechanism 23”. [Comment 48] Line 341-343: Also in the croplands, I would highly doubt that and you have date to prove it – do it! [Response 48] In our original manuscript, we proposed that silicate bedrock might limit microbial activity and EPS production due to its slow weathering rate and limited nutrient release. However, based on further analysis—including variance partitioning and evaluation of resource availability across different land-use types—we found that this explanation is not well supported by our data (e.g., higher MBC than sediment). Therefore, we have removed this sentence “In contrast, silicate rocks, due to their slower weathering rates and limited nutrient release capacities, may lack certain essential soil microbial elements, thus, limiting microbial activities and the generation of EPS 25, 26” from the revised manuscript to ensure that our discussion remains fully grounded in evidence from our dataset. [Comment 49] Line 344: The authors should precisely use and explain which parameters they assume to influence EPS stabilization and then use them all accordingly, not once including more (Line 340), next time less (Line 344) [Response 49] Thank you for your valuable comment. We have carefully reviewed the entire Discussion Section and ensured that all environmental drivers potentially influencing EPS contents are listed consistently throughout. To improve clarity and scientific rigor, we now refer only to variables that show significant relationships with EPS contents based on correlation analysis and results from two-way ANOVA and variance partitioning. This approach helps to maintain consistency in our interpretation. [Comment 50] Line 345-346: Prove it! Is a low pH going along with reduced microbial parameters lower MBC, lower CUE, ….. [Response 50] We examined the relationships among soil pH, microbial parameters, and EPS content across the three bedrock types and summarized the key findings as follows (see also response R4-46): (1) EPS content: Carbonate > Silicate > Sediment (2) EPS-C/MBC: Sediment > Carbonate > Silicate (3) pH: Carbonate > Sediment > Silicate (4) MBC: Carbonate > Silicate > Sediment (5) CUE: Silicate > Carbonate > Sediment (6) WHC: Silicate > Carbonate > Sediment (7) SMC: Silicate > Carbonate > Sediment (8) Ca , clay, and silt contents: Carbonate > Sediment > Silicate e Notably, no significant correlation was observed between soil pH and EPS content (Supplementary Fig. 3), suggesting that pH alone may not directly explain the variation in EPS between bedrock types. Interestingly, although silicate soils had the second-highest EPS and MBC levels, their EPS-C/MBC ratio was the lowest. In contrast, sedimentary soils exhibited both the lowest EPS and MBC values but the highest EPS-C/MBC ratio. Supplementary Figure 3 | Relationship between EPS content, EPS-C/MBC ratio and soil pH. a Relationship between extracellular polymeric substances (EPS) and soil pH. b Relationship between extracellular polymeric substances carbon to microbial biomass carbon ratio (EPS-C/MBC) and soil pH. Different colors represent land use types, while different point shapes represent bedrock types. The solid line indicates the fitted quadratic regression. This pattern may be attributed to stronger water stress in sedimentary soils— indicated by the lowest WHC and SMC—which could trigger greater microbial investment in EPS production. Sedimentary soils have intermediate sand content and the lowest SOC amount the three bedrock types, which may further limit soil water retention and nutrient availability, reinforcing the need for microbial EPS production. Conversely, silicate soils had the highest WHC and SMC, potentially reducing the need for EPS-mediated stress protection and leading to lower carbon allocation to EPS. Additionally, silicate soils had the lowest Ca , clay, and silt contents, possibly providing e the least protection for EPS and thus reducing its short-term retention (Supplementary Table 5). Accordingly, we have revised the original sentence from “Silicate soils had the lowest levels of potentially EPS-binding properties (clay, silt, and, Ca ), and the lowest e EPS production efficiencies which were accompanied by lowest soil pH values eventually reducing microbial activities and decomposition processes” to “Although silicate soils exhibited intermediate levels of both EPS and MBC (Supplementary Table 5), they had the lowest EPS-C/MBC ratio. This suggests that microbes in silicate soils may have allocated proportionally less C toward EPS production or are less conducive for intermittent EPS retention. Three possible explanations can be proposed: (1) Environmental stress in silicate soils may be relatively mild – for example, these soils exhibited the highest SMC and WHC – whereas more severe moisture-related stress in sedimentary soils might have triggered greater EPS production; (2) the lowest levels of Ca and clay (highest sand content) in silicate soils may have provided the least e protection for EPS (Supplementary Table 5); (3) differences in microbial community composition or metabolic strategies may also contribute to the observed pattern. However, we currently lack direct evidence to confirm the third explanation” (Pages 10-11, Lines 294-304). We have also added Fig. 9 and Fig. 10 and supporting analyses in the supplementary materials (Supplementary Table 5). Figure 9. Linear regressions between EPS and soil water properties. a Relationship between EPS and water holding capacity. b Relationship between EPS and soil moisture content. Blue lines indicate linear regression fits with 95% confidence intervals (shaded). The R2 and p-value for each regression are shown on each panel. Each point represents an individual soil sample. EPS, extracellular polymeric substances. Figure 10. Linear regressions between EPS-C/MBC and key soil and microbial parameters. a Relationship between EPS-C/MBC and soil moisture content. b Relationship between EPS-C/MBC and aridity index. c Relationship between EPS-C/MBC and microbial growth. d Relationship between EPS-C/MBC and microbial carbon use efficiency. Blue lines indicate linear regression fits with 95% confidence intervals (shaded). The R2 and p-value for each regression are shown on each panel. Each point represents an individual soil sample. EPS, extracellular polymeric substances; MBC, microbial biomass carbon; C microbial growth. growth, [Comment 51] Line 346-349: The authors did not prove the first step in my point of view, that the bedrock is making the difference in soil properties (not differences in bedrock chemistry – please be precise) – I can find that data. The authors found significant different EPS concentrations, the rest is speculation…. Revise it accordingly [Response 51] Thank you for your valuable comment. We fully understand and appreciate your concern regarding whether the observed differences in soil EPS are truly driven by bedrock type, rather than simply reflecting differences in bedrock chemistry. In response, we have carefully revised the relevant part of the Discussion Section to avoid unsupported assumptions and to base our interpretation more strictly on the data (see response R4-45). Specifically, we performed two-way ANOVA and variance partitioning analyses to quantitatively assess the respective influences of bedrock type and land use on soil physicochemical properties (see Supplementary Table 5). Our results show that bedrock type significantly influences soil properties that are strongly correlated with EPS content, including MBC, MBN, CEC, SMC, Ca , and clay content. These findings, e together with the observed correlations between EPS and these environmental factors, provide data-supported evidence that bedrock-driven differences in soil properties may underlie the variation in EPS content. Additionally, we revised the Discussion Section (Pages 9-11, Lines 259-307) to remove inappropriate language and to ensure consistency with the observed statistical results. We believe this has improved the clarity and reliability of our interpretation. Thank you again for your constructive feedback. [Comment 52] Line 462-463: The authors found a weak negative correlation line 261- 262 – so is it worse pushing it here – or would be better to try to discuss instead of refreshing what others propagated but have been seldom proven. [Response 52] Thank you very much for your insightful comment. We agree that the observed correlation between the EPS-C/MBC ratio and ADI is relatively weak and therefore should be interpreted with caution. Moreover, responses to aridity and drought do not align directly, see response R3-19. To avoid overstating our findings and to better reflect the data strength, we have revised this sentence from “Although this has not yet been demonstrated for soil microbial communities, we demonstrate this adaptive phenomenon on a large scale i.e., reflected by increasing EPS production efficiency with increasing aridity (indicated by a decrease in the aridity index, ADI) and with worsening drought conditions. This same trend was apparent by the negative correlation between EPS production efficiency and soil moisture content across Europe” to “Although not previously demonstrated for soil microbial communities, we show this adaptive phenomenon at a large scale, reflected by increasing EPS-C/MBC along an aridity (ADI) gradient, suggesting microbial adaptation to long-term water-limited environments. This pattern is further supported by the negative correlation between EPS-C/MBC and SMC (Fig. 10). Microbial communities therefore invest in EPS secretion to retain soil moisture under increasing water deficit. However, as measured EPS levels are influenced by production, decomposition, and stabilization processes, the true microbial response requires further investigation” to adopt a more cautious tone. Rather than claiming to demonstrate a confirmed adaptive mechanism, we now describe the observed pattern as a potential trend that warrants further investigation (Pages 12- 13, Lines 369-375). [Comment 53] Line 467-468: refer to the data – where can I find it as a reader – such a figure with this correlation would be nice to see in the supplement! [Response 53] Thank you for your valuable comment. We apologize for the earlier oversight of not including the relationship between EPS and WHC in Fig. 2c. We have now added this correlation to the heatmap in Fig. 2c, provide full visualisation of the relation between EPS and WHC in the new Fig. 9 (see response R3-10) and revised this sentence to directly refer to the relevant data. [Comment 54] Line 331-333: What do the authors mean by “promote adsorption”? I thought the EPS is bound via Ca-bridging!? Clarify [Response 54] Thank you for pointing this out. We acknowledge the ambiguity in our original phrasing. To clarify, we have revised the sentence from “This provides a suitable living environment for microorganisms, but also promotes the adsorption of EPS by minerals and thereby aids with its stabilization and accumulation 20, 21” to “soil minerals (clay) and cations (Ca ) may contribute to the selective retention of EPS within e the soil matrix through multivalent cation bridging between negatively charged sites of EPS and other polymers and minerals5, 11” (Page 10, Lines 267-270). More details on the mechanisms underlying soil EPS stability have been added to Supplementary Discussion 3. Please see below: Supplementary Discussion 3 - Mechanisms of EPS stabilization in soils EPS in soils is stabilized via multiple mechanisms5, 8, 11, including (i) physical occlusion inside microaggregates, (ii) co-precipitation and complexation with Fe/Al, (iii) hydrogen bonding, (iv) hydrophobic interactions, (v) inner-sphere ligand exchange to Fe/Al (oxyhydr)oxides and clays, (vi) outer-sphere electrostatic attraction, and (vii) multivalent cation bridging between negatively charged sites of EPS and those on other polymers and minerals. The importance of these mechanisms differs between main EPS compounds, with EPS polysaccharides mainly bound/stabilized by (ii, iii, v, vii) and EPS proteins via (ii, iii, iv, v, vi, vii). The cation bridging mechanism via Ca2+ (vii) and electrostatic attraction (vi) causes a loosely bound (not strongly stabilized) association, which is reversible; it is this EPS fraction that is targeted by the CER method due to removing Ca2+ by CER and the extraction buffer, weakening electrostatic forces. Binding of EPS by other mechanisms causes weaker binding and stabilization (iii) or stronger binding/immobilization and stabilization (ii, iv, v), but these latter EPS fractions are not targeted or extracted by CER. Since comprehensive studies across EPS components, sources, and soil types are still lacking, this remains poorly understood. In culture experiments, it is also the loosely bound fraction of EPS that is extracted by CER, whereas the tightly bound fraction remains unextracted. [Comment 55] Line 333-335: How did the authors study sorption and stabilization controls on EPS concentrations (maybe I missed that point?) – it can´t be evident from a correlation!!!! Refer to the data that all these properties are highest in the carbonate soils – I would wish to prove that. [Response 55] We fully agree that correlations alone are not sufficient to demonstrate sorption and stabilization controls on EPS contents. In response, we revised the Discussion Section to provide a more data-driven explanation. Specifically, we conducted two-way ANOVA and variance partitioning analyses to evaluate the effects of bedrock type and land use on environmental and microbial factors. Our results showed that carbonate soils exhibited significantly higher levels of Ca , and clay e content compared to soils developed on silicate and sedimentary bedrock (Supplementary Table 5). These properties are known to influence EPS retention via electrostatic interactions and cation bridging, and were also positively correlated with EPS contents in our study. Therefore, we have revised the sentence from “Sorption and stabilization controls on EPS concentrations were also evident from positive correlations between EPS concentration and Ca , clay, silt and Fe , and these properties were also highest in e d carbonate soils” to “This pattern was mirrored in microbial (e.g., MBC and MBN) and soil properties (e.g., CEC, clay, and Ca ), known to promote EPS, all of which were e significantly influenced by bedrock and peaked in carbonate soils. Conversely, sand content – which was lowest in carbonate soils – was negatively correlated with EPS contents (Supplementary Table 5). Based on these findings, we propose that the highest EPS content in carbonate soils is primarily driven by two aspects: (1) an indirect pathway, where highest soil pH and CEC (particularly Ca ) e modulates the soil microenvironment in ways that stimulate microbial activity27, increase microbial biomass (e.g., MBC and MBN) and thereby causes greater overall capacity for EPS production9; and (2) soil minerals (clay) and cations (Ca ) may e contribute to the selective retention of EPS within the soil matrix through multivalent cation bridging between negatively charged sites of EPS and other polymers and minerals5, 11” (Pages 9-10, Lines 260-270). See also response R1-22, R4-45/46, R4-50 on sorption and bedrock controls. [Comment 56] Line 337: The authors should better let us participate in their nebulous explanations, what is meant here by “positive feedback mechanisms”. [Response 56] In this context, the “positive feedback mechanism” refers to the following process: nutrients released from sedimentary rocks (such as NH +) 22 4 stimulate microbial EPS production; the increased EPS enhances microbial resource acquisition and protection (e.g., by retaining moisture and stabilizing enzymes), which in turn further promotes microbial growth and activity - leading to even more EPS production. However, upon further data analysis, we arrived at a new interpretation for the high EPS-C/MBC ratios observed in sedimentary soils: “Interestingly, while carbonate soils exhibited the highest EPS contents, their EPS-C/MBC ratios followed a different pattern, with soils on sedimentary rocks demonstrating the highest EPS-C/MBC ratios (Fig. 7a). Although this ratio does not directly reflect EPS production efficiency – since EPS contents in natural soils result from the balance of microbial production and degradation, modulated by mineral interactions and extraction limitations – it may serve as a proxy for the relative allocation of microbial C assimilates to extracellular non-growth products under steady state conditions. Notably, sedimentary soils had the lowest EPS contents, but the highest EPS-C/MBC ratios, which likely stems from reduced MBC rather than increased EPS contents. Supporting this interpretation, microbial growth-related parameters (e.g., C , MBC, and MBN) growth were consistently lowest in sedimentary soils, which also had the lowest WHC and SMC (Supplementary Table 5). Given the decrease in MBC at lower WHC and SMC (Supplementary Fig. 2), we infer that limited water availability in sedimentary soils may constrain microbial growth and shift C allocation towards EPS formation. This shift may reflect an adaptive microbial strategy to enhance survival and maintain extracellular protection under water-stressed conditions5” (Page 10, Lines 281-294). [Comment 57] Line 350-364: Condense and stick to the data you have. [Response 57] To improve clarity and better align with the data, we have revised the section on land use from “Among the three land-use types, EPS concentrations were highest in grassland soils compared to cropland and woodland soils. Interestingly, as observed with the different types of bedrock, the rankings for EPS production efficiencies and EPS concentrations did not align consistently across land use types. The EPS production efficiencies of croplands and grasslands were similar and higher than those of woodlands. This divergence may have been attributed to large differences in plant belowground C inputs (root system development) accompanied by external nutrient inputs (fertilization) and disturbance (tillage, grazing) in agricultural systems (Supplementary Table S16) 90. Soil EPS increased with fine root biomass along the European transect, indicating that part of the land use driven patterns in EPS concentration were plant input driven. Plant fine root biomass was similar in grasslands and woodlands, and much greater than in croplands, but root morphologies also differ dramatically 90. Grass roots are known to be much thinner and have greater specific root length (length per mass of fine roots), globally leading to much greater fine root length and fine root area in grasslands than in forests, where trees produce thicker roots with less fine root length and area 90. Thinner roots turnover faster and thereby produce larger root necromass inputs in topsoil which adds to greater root exudate inputs in grasslands with their markedly greater root surface area 90” to “Among the three land-use types, EPS contents were highest in grassland soils compared to cropland and woodland soils, although the differences did not reach statistical significance (Fig. 2b). To identify potential drivers of EPS content variation, we found that MBC was significantly affected by land use and showed a pattern consistent with EPS (Supplementary Table 5). This, together with the positive correlation between MBC and EPS (Fig. 2c), suggests that higher MBC may indicate larger microbial populations, thereby representing a greater potential for EPS production and serving as a primary control on EPS content across land-use types. In addition, land-use exerted a stronger influence on soil nutrient status (e.g., SOC, TOP, TP, Mg , and NO -) and fine root traits (FRB and e 3 Root N) than bedrock (Supplementary Table 5). Among these, SOC and TOP were significantly higher in grassland than in cropland and positively correlated with EPS, while root N was also highest in grasslands, whereas FRB peaked in woodlands but remained relatively high in grasslands. These indicators suggest that improved nutrient availability and greater plant inputs (root turnover and exudation) may enhance microbial EPS production87. This interpretation is consistent with previous findings: Redmile-Gordon et al.28 observed the highest EPS contents in grasslands, while Kidinda et al.9 reported higher EPS in fertilized croplands than in forests on nutrient- poor tropical soils. Together, these studies suggest that land-use effects on EPS are primarily mediated by plant inputs and nutrient availability. Conversely, the lowest MBC and SOC observed in cropland soils may reflect soil degradation or organic matter depletion caused by long-term intensive management practices such as tillage, which could in turn contribute to the reduced EPS levels. For instance, frequent tillage can disrupt soil structure and aggregates, thereby reducing soil organic matter content10. On the other hand, although croplands had the highest clay and exchangeable Ca2+ contents—factors potentially favouring short-term EPS retention—their EPS levels were lowest. This suggests that limited labile C availability, linked to lower SOC and FRB in croplands, may play a more decisive role in constraining microbial EPS content across the investigated soils. Substantial differences in the composition and function of soil microbial communities under different land use types88 may also cause differences in EPS formation and decomposition89. While microbial diversity was not investigated in this study, in accordance with investigations of legacy vs current management effects on EPS28, it is primarily the interplay between plant inputs and anthropogenic management that causes these differences in total EPS and EPS protein contents”. As the effect of land use on EPS was not significant, this part of the discussion has accordingly been moved to Supplementary Discussion 4. We have retained a brief description in the main text: “Meanwhile, EPS contents did not differ significantly among land use types but tended to be highest in grasslands, with microbial biomass, nutrient availability, and plant inputs mediating the land-use- based variation; in contrast, EPS-C/MBC ratios peaked in croplands, likely reflecting enhanced microbial EPS investment under water limitation (Supplementary Discussion 4)” (Page 11, Lines 308-311). See also responses R1-27, R3-13, and R4-57, R4-58, and R4-59. [Comment 58] 366-368: Please prove it and how does that fit with the discussion beforehand? Did you have cropland on silicate bedrock!? [Response 58] Following your suggestion in comment R4-39 and your specific point in R4-57 to “stick to our data,” we have removed vague explanations that were not directly supported by our dataset (e.g., long-term fertilization effects). Importantly, we do not have accurate fertilization data for cropland sites. Therefore, we re-analyzed the data using two-way ANOVA and variance partitioning, and reassessed the values of environmental and microbial factors across different land-use types and their correlations with EPS (Supplementary Table 5). Based on these results, we have now provided a revised explanation for the observation that croplands had the highest EPS- C/MBC. Specifically, we have replaced the original sentence “Despite lower plant root C inputs in croplands due to the reduced root system development in cropping systems, on a microbial biomass basis, EPS production efficiency was highest, likely due to relaxed nutrient constraints of microbial activities through long-term fertilization” with “Interestingly, the ranking of EPS-C/MBC did not mirror that of EPS contents, with croplands showing the highest EPS-C/MBC, followed by grasslands and woodlands (Fig. 7b). Given that both EPS and MBC were lowest in cropland soils, this highest EPS-C/MBC ratio suggests a greater microbial investment in EPS production per unit biomass. This may be a response to increased water stress in croplands, as indicated by significantly lower WHC and SMC compared to woodlands and grasslands (Supplementary Table 5)” (Supplementary Discussion 4). [Comment 59] Line 368-370: Do you prove if the lowest plant root input in cropland caused the lowest MBC levels!? I always thought it is due to the overall management (mechanical and chemical interventions)! Maybe the croplands are just lowest in EPS stabilization properties? Just sarcastic joke… please revise your discussion along your data and what you can prove and not prove. Instead of interpreting your data once like that and then the other way around as it better suits your story. [Response 59] We acknowledge that in the original manuscript, we did not provide direct evidence showing that the low fine root biomass (FRB) in croplands led to the reduced microbial biomass carbon (MBC). Indeed, as you pointed out, the overall land management practices in cropland, such as mechanical disturbance, may also contribute to the lower MBC levels. We have revised the discussion accordingly to reflect this possibility. See also our response to land use related effects on EPS in R1-27, R3-13 and R4-57. In addition, after deeper analysis of the data, we now attribute the highest EPS- C/MBC ratio in croplands — despite both EPS and MBC being the lowest among the land-use types — to potential microbial stress responses to limited soil water availability. This is supported by significantly lower water holding capacity (WHC) and soil moisture content (SMC) in cropland soils compared to the other land-use types. As for your suggestion regarding potential differences in EPS retention, we also explored this aspect. Interestingly, although cropland soils exhibited highest clay and exchangeable Ca2+ (Ca ) — both commonly considered important for EPS e retention — their EPS contents remained low. This may indicate that, in this case, stimulatory effects of soil nutrient status on microbial EPS production may outweigh those of the retention of EPS. We have accordingly added this sentence “Conversely, the lowest MBC and SOC observed in cropland soils may reflect soil degradation or organic matter depletion caused by long-term intensive management practices such as tillage, which could in turn contribute to the reduced EPS levels. For instance, frequent tillage can disrupt soil structure and aggregates, thereby reducing soil organic matter content10. On the other hand, although croplands had the highest clay and exchangeable Ca2+ contents—factors potentially favouring short-term EPS retention—their EPS levels were lowest. This suggests that limited labile C availability, linked to lower SOC and FRB in croplands, may play a more decisive role in constraining microbial EPS content across the investigated soils. Substantial differences in the composition and function of soil microbial communities under different land use types88 may also cause differences in EPS formation and decomposition89. While microbial diversity was not investigated in this study, in accordance with investigations of legacy vs current management effects on EPS28, it is primarily the interplay between plant inputs and anthropogenic management that causes these differences in total EPS and EPS protein contents” in Supplementary Discussion 4 and revised this sentence from “However, low plant root C inputs in croplands caused the lowest MBC levels and therefore, even at the highest microbial EPS production efficiencies, the lowest EPS concentrations” to “Interestingly, the ranking of EPS-C/MBC did not mirror that of EPS contents, with croplands showing the highest EPS-C/MBC, followed by grasslands and woodlands (Fig. 7b). Given that both EPS and MBC were lowest in cropland soils, this highest EPS-C/MBC ratio suggests a greater microbial investment in EPS production per unit biomass. This may be a response to increased water stress in croplands, as indicated by significantly lower WHC and SMC compared to woodlands and grasslands (Supplementary Table 5)” in Supplementary Discussion 4. [Comment 60] Line 373-374: How is agricultural management reducing stabilization properties? And if you find overall lower MBC, how will the management increase EPS degradation? [Response 60] We acknowledge that the previous version of the manuscript did not sufficiently explore the underlying data to support the claim that agricultural management reduces EPS stabilization and accelerates EPS degradation. After conducting a two-way ANOVA and variance partitioning, and examining the environmental and microbial factor values across the three land-use types, we found that this explanation is not well supported by the data. In fact, cropland soils exhibited relatively high clay content (which generally favours EPS stabilization) alongside low MBC. Therefore, we have removed the sentence “These factors contribute to reduced formation and stabilization and accelerated degradation of EPS 91” from the manuscript. Instead, we added the Supplementary Discussion 4 to provide new explanations for the observed variations in EPS content and EPS-C/MBC ratio among the land-use types based on our data analysis. See responses R1-27, R4-57 and R4-59 above. [Comment 61] Line 382-385: Which difference reflects what! Explain! [Response 61] What we intended to convey is that the content of EPS polysaccharides responds more strongly to changes in bedrock type, while EPS protein content is more responsive to land-use change. We realize that our original wording may have caused confusion, and we have revised the sentence from “This difference reflects the different elemental demands (C, or C plus N) and controls of the biosynthetic pathways of EPS polysaccharides and EPS proteins in microbial ecosystems 23, and the different interaction mechanisms with organic and mineral surfaces of EPS polysaccharides and EPS proteins promoting their binding, stabilization and accumulation” to “Moreover, distinct environmental dependencies and biosynthetic pathways of EPS polysaccharides and EPS proteins caused their contents to be differentially by bedrock and land use, respectively (Supplementary Discussion 5)” (Page 11, Lines 311-314). Further discussion of the mechanisms behind the contrasting responses of EPS polysaccharides and proteins to land-use type and bedrock has been included in Supplementary Discussion 5. Please see below: Supplementary Discussion 5 - Bedrock vs. land use: drivers of specific EPS components A more detailed analysis revealed that it was primarily the bedrock type that affected the contents of EPS polysaccharides, while the type of land use influenced the contents of EPS proteins (Fig. 3). This divergence likely stems from their distinct environmental dependencies and biosynthetic pathways. Based on our data, bedrock type significantly influenced microbial biomass (MBC and MBN), soil texture (clay content), CEC, and exchangeable Ca2+ (Supplementary Table 5), all of which are positively associated with EPS polysaccharides content. In contrast, land use significantly influenced MBN, and had a stronger effect on microbial q and soil Growth nutrient availability, such as soil NH +, NO -, and TOP, as well as on SOC 4 3 (Supplementary Table 5), which plays a critical role in microbial protein synthesis and was positively related to EPS protein. This is consistent with our random forest analysis showing that EPS polysaccharides were mainly driven by Ca , MBN, and SOC, e whereas EPS proteins were predominantly influenced by MBN, SOC, and q (Fig. Growth 4b, c). These results indicate that while both EPS polysaccharides and EPS proteins are influenced by microbial abundance and nitrogen availability (MBN) as well as soil C status (SOC), EPS polysaccharides are closely associated with soil Ca2+, highlighting their role in reinforcing soil structure, whereas EPS proteins are more strongly linked to microbial biosynthetic activity (q ). Additionally, based on the principle of the Growth CER method, variations in Ca2+ concentrations induced by different bedrock types may influence EPS extraction efficiency and thus affect the measured EPS contents36. Although a preliminary experiment was conducted to optimize the extraction procedure across soil types, variability in extraction efficiency cannot be fully excluded. However, since only EPS polysaccharides, but not EPS proteins, showed significant variation with bedrock type, this indicates that the contrasting patterns are unlikely to result solely from methodological bias, but rather reflect differences in environmental or microbial regulation of EPS components. [Comment 62] Line 386: How can the authors come up with an EPS accumulation!? You did not study that, or? [Response 62] Thank you for your valuable suggestion. As our study did not include multi-time-point measurement of EPS, we agree that we cannot provide direct evidence for EPS accumulation. To improve the accuracy and clarity of our statement, we have removed the sentence “The phenomenon of differential controls of EPS polysaccharide and EPS protein accumulation is therefore triggered by the selective regulation of microbial metabolic dynamics leading to EPS compound biosynthesis and secretion and differences in their stabilization mechanisms” accordingly. [Comment 63] Line 388-393: here the authors open up another discussion box – which they also can´t prove – delete – unnecessary for the study [Response 63] Thank you for your helpful comment. We have removed this sentence “This differential accumulation mechanisms are thought to have strong repercussions on the properties of EPS like its stickiness and adhesion, mechanical stability (Supplementary Fig. S2), ion binding capacity and hydration potential which are related to the ratio of EPS protein: EPS polysaccharides 92, 93. However, studies on the EPS protein-to-polysaccharide ratio have primarily been conducted in marine environments, with no research available in the context of soils” from the revised manuscript to maintain focus and clarity. [Comment 64] Line 398-400: It would help if the authors include a precise description of the calculation. [Response 64] Thank you for your helpful suggestion. We have now included a clear and detailed description of the EPS-C calculation in the Methods Section (Pages 17-18, Lines 541-571). For further explanation regarding the derivation of the conversion factors, please also refer to our response R4-4. [Comment 65] Line 401: Prove that number! [Response 65] The C content of EPS polysaccharides (39.1%) used in our calculation was derived as the arithmetic mean of the C content of four representative standard compounds commonly assigned as microbial and/or plant EPS compounds: hyaluronic acid (37.5% C), xylan (40.5% C), pectin (38.3% C), and arabinogalactan (40.2% C). While we acknowledge that this estimation cannot fully reflect the structural and compositional diversity of microbial EPS in soils, it provides a reproducible and reasonable approximation for quantifying EPS-C at larger scales. We have clarified this point in the Methods Section (Pages 17-18, Lines 541-571), see our response R4-4. [Comment 66] Line 401-404: But microbes produce a variety of EPS sugars and proteins – even single microbes can produce different EPS constituents – how does that relate to your estimation based on one species!? [Response 66] Thank you for your insightful comment. Indeed, we fully acknowledge that soil microbes produce a wide variety of EPS polysaccharides and EPS proteins, and even individual strains can synthesize diverse EPS polysaccharide forms and likely 100s of EPS-related exoproteins. In our study, the estimation of the carbon content of EPS proteins (50.7%) was based on the average amino acid composition and weighed amino acid C:N ratio of microbial proteins, using the amino acid composition of the yeast proteome as a representative dataset 51, and assuming a global average nitrogen content of 16% in proteins 65, 66. This allowed us to calculate the corresponding carbon content based on average proteinogenic amino acid C:N ratios. See also response in R4-4. This method provides a reproducible estimation. However, we fully agree that it cannot capture the full biochemical diversity and complexity of microbial EPS in soils. Given the growing interest in soil EPS and its roles in soil functioning, our intention was to provide an approximate but practical estimate of total EPS amounts and associated carbon pools in soil systems. We believe such estimates, while approximate, can capture the broad patterns of EPS distribution and their environmental drivers across large scales. We have clarified this in the Methods Section (Pages 17-18, Lines 541-571)."}, "author_response": ""}]

Decision letter