Impact of polyacrylic acid as soil amendment on soil microbial activity under different moisture regimes

Impact of polyacrylic acid as soil amendment on soil microbial activity under different moisture regimes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Impact of polyacrylic acid as soil amendment on soil microbial activity under different moisture regimes Christian Buchmann, Simon Rudolph, Janina Neff, Zacharias Steinmetz This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6225306/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Jun, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Polyacrylic acid (PAA), a synthetic superabsorbent polymer (SAP), enhances the maximum water holding capacity (WHC max ), stability, and aeration of soil but may directly or indirectly impact the soil microbiome by altering soil properties. However, respective studies on its effects on microbial activity in terms of respiration and functional diversity remain scarce. In this study, we examined the impact of PAA on soil microbial activity in a sand and loam treated with PAA at three concentrations (25, 250, 2500 mg Kg − 1 ) and either incubated under constant moisture or ten drying-rewetting cycles. During incubation, soil WHC max , pH, and microbial activity were measured via headspace CO 2 and MicroResp assay. PAA increased WHC max in both soils and remained stable, except in loam under static moisture. Initially, PAA lowered pH in both soils, which persisted only in sand and disappeared in loam after one week. Further, drying-rewetting cycles raised pH in both soils compared to static conditions. PAA suppressed substrate-induced respiration (SIR) for carbohydrates, amines, and carboxylic acids, particularly in the sand, where high concentrations led to up to 100% suppression. Responses in the loam varied: drying-rewetting cycles increased, while static conditions reduced microbial respiration at higher PAA concentrations, respectively. Overall, PAA reduced microbial activity in sand, whereas moisture regimes and soil texture were dominant factors in loam. This highlights the dual impact of SAPs: improving water retention in a certain period, while potentially reducing soil microbial activity and nutrient cycling, depending on soil type, application rates, and environmental conditions. In the long term. Biological sciences/Microbiology Earth and environmental sciences/Biogeochemistry Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Natural hazards Earth and environmental sciences/Solid earth sciences Physical sciences/Materials science Polyacrylic acid Soil amendment Soil microbial activity Substrate-induced respiration Soil water holding capacity Drying-rewetting cycles Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Superabsorbent polymers (SAPs) can absorb and retain large amounts of water or aqueous solutions, which makes them commonly used as soil conditioners to alter soil properties, such as the maximum water holding capacity (WHC max ), soil structural stability, as well as the availability of nutrients, fertilizers, and pesticides [ 1 , 2 ]. Based on their properties and synthesis methods, SAPs can be categorized by their origin (natural, synthetic, or hybrid) and crosslinking type (chemical or physical bonds) [ 3 ]. In this context, polyacrylic acid (PAA) is one of the most frequently used synthetic SAPs due to its high water absorption (swelling) capacity, typically ranging between 300–500 g water g − 1 dry polymer [ 4 ]. However, the water absorption capacity of SAPs can be significantly impaired by the presence of certain ions, particularly multivalent cations (e.g., Ca²⁺, Al³⁺), through cation-mediated crosslinking [ 5 ]. This process occurs when multivalent cations interact with anionic groups on the polymer chains, forming additional crosslinks within the network structure and resulting in reduced water absorption capacity and altered key physicochemical properties, including mechanical strength, diffusion rates, and pH sensitivity [ 6 – 8 ]. While the beneficial properties of superabsorbent polymers (SAPs) are well-documented, their introduction into soil systems may pose several risks and challenges. A major concern is the persistence of PAA due to its extremely low biodegradation rates of only 0.2–0.5% y − 1 in soil [ 9 ]. In contrast to naturally occurring SAPs such as gellan, alginate, or mucilage, this persistence raises the potential for long-term accumulation, with reported concentrations reaching up to 10 g SAP Kg − 1 soil [ 6 ]. Moreover, it has been shown that the positive effects of SAPs on soil WHC can diminish within three months after application, necessitating frequent reapplications to maintain effectiveness in arid and semi-arid soils and thereby further increasing concerns about the accumulation and impact of PAA in soil [ 10 ]. Additionally, soil moisture dynamics, such as regular drying-rewetting cycles, can significantly alter the functionality of SAPs, e.g., leading to reduced water absorption capacity over time [ 11 ]. Aging processes, including chemical, photolytic, and mechanical transformation and degradation, might further contribute to the potential fragmentation of PAA into smaller particles. These fragments can get into deeper soil layers or into neighboring ecosystems with potential negative effects on the environment [ 12 ]. While PAA is well-recognized for its beneficial impacts on various soil physicochemical properties, the consequences of its persistence, accumulation, and aging on soil microbial activity remain largely unknown [ 6 ]. Given the essential role of soil microbial activity in nutrient cycling, organic matter decomposition, and overall soil health [ 13 , 14 ], it is crucial to consider how synthetic SAPs such as PAA might affect, e.g., soil microbial diversity, metabolic functioning, and respiration dynamics to better understand the long-term implications on soil ecosystems. On the one hand, PAA may disrupt or alter microbial processes by altering soil structure and porosity [ 15 , 16 ], which potentially affects the availability of microbial habitats, water distribution, and oxygen diffusion throughout the soil. On the other hand, the chemical properties of PAA, particularly its capability to form complexes with essential nutrients, its presence as a carbon source, and its potential influence on soil pH might also affect the microbial growth and their metabolic activity [ 17 , 18 ]. Thus, its persistence and accumulation potential could make PAA a long-term stressor to microbial communities, altering their functional capabilities and community dynamics through adaptive responses over time. Soil microbial respiration can be divided into autotrophic respiration from plant roots and associated microbes using self-produced energy and heterotrophic respiration from soil microbes decomposing organic matter (OM) [ 19 ]. Since heterotrophic respiration is heavily influenced by environmental factors such as soil moisture, temperature, carbon availability, and pH [ 20 , 21 ], any disturbances or amendments might lead to the alteration of microbial activity and soil respiration dynamics. Basal respiration, typically measured via CO 2 release, primarily results from substrate availability in soil and provides fundamental information on microbial physiology and maintenance requirements. It thus serves as a measure of metabolic activity without quantifying the active microbial activity, as only the currently active microbes involved in respiration are recorded. In contrast, substrate-induced respiration (SIR) via the application of various substrates (e.g., glucose) can activate a broader spectrum of the soil microbiome, including previously dormant taxa [ 22 , 23 ]. This approach allows a more detailed assessment of microbial activity and functional diversity in soil with the quantity and range of utilized carbon sources reflecting microbial biomass abundance and community functional adaptability. Despite the key role of microbial activity for diverse soil processes and soil properties, the specific interactions with and effects of PAA are subject to current research, especially with respect to soil moisture dynamics. This is mainly because most of the available studies are limited to the effect of SAPs on basic soil properties important for agriculture, like aggregate stability, porosity, OM content, and nutrient availability [ 24 ]. Consequently, we aimed to gain first insights into the concentration-, time-, and moisture dynamic-dependent effects of PAA on soil microbial activity and soil functional diversity. For this, a 10-week incubation experiment was performed with two soils, a loam and a sand, which were both treated with PAA at three different concentrations (25, 250, and 2500 mg PAA Kg − 1 dry soil) and subjected to either constant moisture or drying-rewetting conditions. Throughout the incubation, both substrate-induced and basal soil respiration were recorded using MicroResp and headspace CO 2 measurements. In addition, the maximum water-holding capacity (WHC max ) and the pH of the soils were monitored and changes in the soil structure were inveistigated using scanning electron microscopy (SEM). We expected that crosslinking between PAA molecules, driven by soil constituents such as polyvalent cations, along with PAA sorption to soil minerals and soil organic matter (SOM), will reduce the water absorption capacity of PAA in both soils. These effects should be further intensified by repeated drying and rewetting cycles. We hypothesized that increasing PAA concentrations will initially increase the WHC max of the PAA-treated soils; however, this effect should diminish over time, particularly when subjected to moisture dynamics. We propose that PAA-induced effects on soil pH and water binding will significantly modulate microbial activity: on the one hand, low PAA concentrations should enhance microbial respiration by improving water availability, whereas, on the other hand, high PAA concentrations should suppress respiration due to reduced soil pH and stronger water binding. Since PAA increases water retention during drying events and can thus alleviate drought stress, we expect that negative effects on soil microbial activity due to drying-rewetting dynamics will be mitigated. Negative effects of PAA and moisture dynamics, both individually and in combination, should be reflected in changed substrate usage patterns, in which simpler, more readily available carbon sources are preferred over complex compounds. However, since we assume that PAA will lose its functionality over time due to aging processes such as cementation accelerated by the drying-rewetting cycles [ 6 , 25 ], the respective effects on soil microbial respiration should decrease more rapidly under cyclic than static moisture conditions. Materials and methods Soil samples and sample preparation Two well-characterized reference soils (Lufa 2.1 and 2.4) from the Agricultural Analysis and Research Institute Speyer (LUFA, Speyer, Germany) were used in this study as typical agricultural soils. Their textures are classified as sand (Lufa 2.1) and loam (Lufa 2.4) with a pH of 4.6 and 7.5, and an organic carbon content (C org ) of 0.6% and 1.8%, respectively. An overview of selected soil physicochemical properties is presented in Table 1 . Table 1 Selected physicochemical properties of the two investigated soils Parameter Lufa 2.1 Lufa 2.4 Type sand loam Sand (%) 88.2 33.1 Silt (%) 8.4 42.2 Clay (%) 3.5 23.7 C org (%) 0.6 1.8 N tot (%) 0.06 0.23 pH (0.01M CaCl 2 ) 4.6 7.5 CEC (meq 100 g -1 ) 2.9 17.4 WHC max (g 100 g -1 ) 30 47 Bulk density (g cm -3 ) 1.47 1.18 Table 1 The soils were oven-dried at 30°C for 4 days, subsequently spiked with high-weighted, linear polyacrylic acid (PAA) (M v = 4.000.000 g mol − 1 ; ~ 0.1% cross-linkage) (Sigma-Aldrich, Germany) at three concentrations (25, 250 and 2500 mg PAA Kg − 1 ), and manually homogenized for 10 minutes before moistening. Furthermore, control soils without PAA were prepared accordingly. The samples were subdivided into two groups based on the soil moisture conditions during the incubation time (constant moisture and drying-rewetting conditions). Half of the samples underwent ten drying-rewetting cycles, while the remaining samples were kept at static moisture conditions at 40% WHC max for the entire 10-week incubation period. All ten drying-rewetting cycles involved 1) a rapid (re)wetting event with ultrapure water, followed by 2) a three-day incubation period, and 3) a four-day drying phase at 30°C to complete dryness. At the cycles 0, 3, 5, and 10, corresponding to the respective incubation weeks, soil replicates for each treatment and control were taken and investigated for physicochemical properties and soil microbial activity. To improve readability, the term ‘measurement point’ (MP) is used to include soil samples incubated under constant moisture conditions as well as cyclically dried and remoistened (e.g., measurement point 3 depicts incubation week 3 for the constant and the third drying-rewetting cycle for the cyclic soil samples, respectively). Additionally, pure PAA hydrogel was prepared to evaluate its swelling potential in the different soil solutions and demineralized water by allowing dry PAA powder to form a completely swollen hydrogel for 48 h with an excess of soil water (or demineralized water), which was extracted from the respective soils for 30 minutes at 2900 rpm using a MegaStar4.0 centrifuge (VWR, Germany) and 3D-printed polymer falcon tube centrifugation inserts [ 26 ]. After 48 h, excess solution was separated from the swollen PAA hydrogel by centrifugation at 1000 × g for 20 min and the hydrogels were weighed to determine the amount of adsorbed solution per g dry PAA powder according to [ 27 ]. Soil physicochemical characterization WHC max (mL 100 g − 1 dry soil) of the soil samples was determined gravimetrically using the funnel method [ 28 ] based on the weight difference between the wet soil samples (S W / 100% WHC max ) after 4 hours of saturation and 14 hours of gravitational draining, and the corresponding dry soil samples (S D / 0% WHC) after 4 days of drying at 105°C (Eq. 1 ). $$\:{WHC}_{max}=\frac{{S}_{W}-{S}_{D}}{{S}_{D}}*100$$ 1 Soil pH was measured using a multimeter (Consort, Belgium) at the measurement points 0, 3, 5, and 10 following PAA addition for both soils to monitor changes in soil acidity under the different moisture regimes. Microbial activity MicroResp Soil microbial respiration, including both basal and substrate-induced respiration, was measured using the MicroResp method [ 29 ]. For each combination of soil type, PAA concentration, soil moisture condition, and measurement point, a 96-deepwell plate was prepared. The soil masses per well were 0.60 ± 0.01 g for sand and 0.50 ± 0.01 g for loam, respectively. For SIR measurements, eight different carbon substrates were used, which are representative due to their ecological relevance, their known occurrence in the soil environment (e.g. plant root exudates) and their ability to provide a sufficient range of structural complexity: Glucose (GLU), Galactose (GAL), L-alanine (ALA), N-acetylglucosamine (NAGA), α-cyclodextrin (ACYC), Trisodium citrate (CIT), ɣ-aminobutyric acid (GABA), and ultrapure water (WAT) as control. This resulted in 12 replicates per substrate and plate. For the analysis, the substrates were grouped into carbohydrates (GLU, GAL, ACYC), amines (ALA, NAGA, GABA), and carboxylic acids (CIT). Before substrate addition, the soils were preincubated at 40% WHC max for three days. Substrate application to each well resulted in the addition of 30 mg C ml − 1 soil water and raised the soil moisture to 60% WHC max . CO₂ emissions were measured after 6 hours using a pH color reaction with cresol red as the indicator in the agar gel of the 96-well microplates that covered the deepwell plates during incubation. Light absorption at 572 nm, measured using a microplate spectrophotometer (Infinite M200, Tecan, Switzerland), was used to quantify the color change in the indicator gel due to the evolved CO 2 . Non-linear calibration data were used to convert the changes in light absorbance before and after the 6-hour incubation into respiration rates (µg CO 2 -C g⁻¹ soil h⁻¹). SIR was calculated as the difference between the basal respiration rate (WAT) and the respiration rates from the various carbon sources. SIR values for each substrate, along WAT, were summed to determine the total substrate-induced respiration (SIR tot ). Additionally, the variation coefficient of the SIR values was calculated. The respiratory response to the substrate added reflects the proportion of active microbial biomass that is correspondingly able to use the respective carbon source. Headspace CO measurements Headspace CO 2 measurements were conducted to obtain basal soil respiration by assessing the CO 2 concentration evolved in the headspace of the soil samples placed in incubation jars. Measurements were conducted according to [ 30 ] using a portable Los Gatos greenhouse gas analyzer (Los Gatos Research Inc, ABB Ltd, Switzerland) in a closed-loop setup. For this, the incubation jars were equipped with a Luer-lock connector, a three-way valve, an injection cap and two gaskets. This setup allowed headspace sampling without a permanent septum connection, reducing CO 2 loss. A preliminary experiment determined the CO 2 loss of the jars (n = 5; 30 ± 6 ppmv CO 2 h⁻¹), which was used as correction factor in the main experiment. The headspace measurements included three days of respiration, starting with each rewetting of a drying-rewetting cycle. Static samples were vented during the four-day drying period of the cyclic samples. Prior to the removal of the sampling volume (V s = 500 µL), the headspace of the jars was homogenized by mixing the volume with a syringe attached to the three-way valve. The internal volume of the closed-loop setup (V l ), and thus the dilution factor, was determined prior to each measurement point using triplicate injections of standard gas with a known CO 2 concentration (20,000 ± 400 ppmv). The CO 2 concentration of the samples (X s ; CO 2 in ppmv) was calculated according to Eq. 2 as the difference (ΔX) between the baseline gas concentration before the injection (X 0 ) and the average equilibrium concentration (30 s) after injection (X i ). $$\:{X}_{s}=\frac{{V}_{l}}{{V}_{s}}\varDelta\:X+{X}_{i}$$ 2 Assuming standard conditions (P = 1 atm, T = 293.15 K) and knowing the partial volume of CO 2 in the samples (V CO2 = ppmv x 10 − 6 * V air ), the headspace volume (Sand: V air = 107.5 mL; loam: V air = 104.2 mL), and the universal gas constant (R = 0.0821 L atm K − 1 mol − 1 ) the ideal gas law was applied to convert ppmv into moles (n) per headspace. Using the molar mass of CO 2 (M = 44.01 g mol − 1 ), the soil dry weight (m) and incubation time (t), the results were expressed according to Eq. 4 in µg CO 2 -C g − 1 soil h − 1 and thus comparable to the results obtained from the MicroResp method. $$\:x=\frac{n*M}{t*m}$$ 4 Scanning electron microscopy imaging To qualitatively assess the effect of PAA on soil (micro)structural features scanning electron microscopy (SEM) images were taken with a FEI Quanta 250 ESEM (FEI Company Hillsboro, United States) using a secondary electron detector (SED) under high vacuum (< 10 − 4 Pa). Prior to the measurements, the samples were coated with a 30 nm thick layer of gold with a Quorum Q150R S sputter coater (Quorom Technologies Ltd, United Kingdom). The air-dried soil samples of measurement point 0 and 10 (both cyclic and static), either untreated or at 2500 mg PAA Kg − 1 soil were exemplary selected for comparison. Statistical analysis Data analysis was conducted using R version 4.3.0 [ 31 ], employing a comprehensive statistical approach to examine soil parameters and microbial responses. A three-way analysis of variance (ANOVA) was used to evaluate the effects of PAA concentration, experimental time, and soil moisture regimes (sample type) on WHC max , soil pH, and microbial respiration results (stats package). Statistical assumptions were tested including normality of residuals using Q-Q plots and Shapiro-Wilk tests (stats package), homogeneity of variances through Levene's test (car package), and linearity via interaction plots. Post-hoc comparisons were performed using the Tukey HSD test (stats package). The F-value derived from the ANOVA represents the ratio of inter-group to intra-group variance, measuring the relative impact of each factor on the observed variables. It ranges from 0 to positive values, with higher F-values suggesting a stronger effect. The corresponding p-value assesses the significance of the respective effects, with p < 0.05 indicating statistical significance. Omega squared (ω²) was further calculated as an unbiased effect size estimate for each factor, ranging from 0 to 1, with higher values indicating a stronger influence of the independent variable on the dependent variable. For the headspace respiration data, a repeated measures ANOVA was applied (stats package), accounting for multiple measurements of the same sample over time. A principal component analysis (PCA) was conducted to investigate relationships among soil physicochemical properties and microbial respiration variables (FactoMineR and factoextra packages). Continuous variables were standardized, and treatment conditions were incorporated as supplementary qualitative variables. The analysis was visualized through a biplot with 95% confidence interval ellipses, revealing complex interactions between experimental parameters. Detailed statistical parameters, including F-values, p-values, and ω², are presented in Tables 2–4 of the supplementary information (SI). Results Maximum water holding capacity and soil pH WHC max measurements showed significant effects of PAA addition in both soils (Fig. 1 and Table 2a in the SI). The swelling capacity of freely swollen PAA in extracted soil solutions was 56 ± 0.2 mL g − 1 and 47 ± 0.2 mL g − 1 for the sand and loam, respectively, and was thus significantly lower than in demineralized water (76.8 ± 0.1 mL g − 1 ). For the sand, PAA concentration was the most significant factor (ω 2 = 0.79) affecting the WHC max variability (p < 0.00001, df = 3). Figure 1 Already at measurement point 0, increasing PAA concentrations significantly increased WHC max about 22%, from 25.8 ± 0.7 mL 100 g⁻¹ soil at 0 mg PAA Kg − 1 soil to 31 ± 1 mL 100 g⁻¹ soil at 2500 mg PAA Kg − 1 soil. This effect persisted throughout the whole incubation time and for both cyclic and static soil moisture conditions. In addition, neither the incubation time, nor the number of drying-rewetting cycles, nor the soil moisture dynamics in general significantly affected the WHC max of the sand. For the loam, the PAA concentration (ω² = 0.13; p = 0.0004, df = 3), the interaction between PAA concentration and sample type (ω² = 0.12; p = 0.0006, df = 3), and sample type alone (ω² = 0.03; p = 0.0032, df = 1) were the primary explanatory variables for WHC max variability. At measurement point 0, PAA significantly increased WHC max about 12.5%, from initially 47.0 ± 0.5 mL 100 g⁻¹ soil without PAA to 52.8 ± 0.6 mL 100 g⁻¹ soil at the highest PAA concentration. This increase remained significant under drying and rewetting, without further effects due to increasing cycles. Under static soil moisture conditions, the initial effect of PAA decreased over time, with no significant differences in WHC max compared to the control by measurement point 3. Although not statistically significant, WHC max showed a decreasing trend with increasing PAA concentrations in these weeks. Loam treated with the highest PAA concentration (2500 mg PAA Kg⁻¹ soil) and subjected to drying-rewetting cycles revealed a significantly higher WHC max after 10 weeks compared to the respective soil incubated at constant soil moisture. When comparing the average increase in WHC max between the control and the highest PAA concentration for the cyclic samples, no significant differences (p = 0.46) were observed between the sand (5.5 ± 0.2 mL 100 g⁻¹ soil) and the loam (4.9 ± 0.6 mL 100 g⁻¹ soil). Soil pH PAA significantly (p < 0.001, df = 3) affected soil pH in both soils (Fig. 2 and Table 2b in SI). In the sand, PAA significantly reduced the soil pH directly after application from 4.52 ± 0.02 at 0 mg PAA Kg⁻¹ soil to 3.89 ± 0.01 at 2500 mg PAA Kg⁻¹ soil. Although the pH successively re-increased over time, its reduction remained significant. The sand subjected to drying-rewetting cycles showed significantly higher pH values at measurement point 3 and after compared to the samples incubated at constant moisture conditions. The most significant factors for soil pH variability were the PAA concentration (ω² = 0.37) and the incubation time (ω² = 0.34). Figure 2 In the loam, PAA significantly reduced soil pH from initially 6.94 ± 0.02 at 0 mg PAA Kg⁻¹ soil to 6.42 ± 0.02 at 2500 mg PAA Kg⁻¹ soil. In contrast to the sand, the pH-reducing effect of PAA decreased over time, with pH values slightly (re-)increasing from measurement point 5 until the end of the experiment. At measurement point 10, the soil pH at constant moisture conditions increased from initially 6.63 ± 0.01 at 0 mg PAA Kg⁻¹ soil to 6.71 ± 0.01 at 2500 mg PAA Kg⁻¹ soil, whereas drying-rewetting cycles revealed pH changes from 6.82 ± 0.02 at 0 mg PAA Kg⁻¹ soil to 6.91 ± 0.02 at 2500 mg PAA Kg⁻¹ soil. Thus, the drying-re-wetting cycles led to significantly higher pH values from measurement point 3 onwards than under static soil moisture conditions. The most significant factors for soil pH variability were soil moisture condition (ω² = 0.40, p < 0.0001, df = 1) and the interaction of PAA concentration and time (ω² = 0.30, p < 0.0001, df = 9). All in all, the sand exhibited a higher pH reduction in response to PAA addition compared to the loam. Furthermore, the pH reduction in the sand was significant throughout the entire incubation time, whereas the loam showed an acidifying effect over time. At the end of the experiment (measurement point 10), both soils subjected to drying-rewetting cycles showed significantly higher pH values compared to the respective soils incubated at static moisture conditions. Soil microbial activity and functional diversity Headspace CO 2 measurements were performed to assess the basal respiration activity of the two investigated soils as function of the incubation time, soil moisture regimes and PAA concentration (Fig. 3 a). On the one hand, regardless of the incubation conditions (constant soil moisture vs. drying-rewetting cycles) and PAA concentration, both soils showed the same trend in terms of a high CO 2 release in the first week of incubation (measurement point 0), followed by a drastic drop and a constant respiration level from measurement point 3 onwards. Consequently, the incubation time was the primary factor (ω² = 0.86, p < 0.0001, df = 3 for sand; ω² = 0.94, p < 0.0001, df = 3 for loam) explaining the variability in basal respiration of both soils (Table 3 in SI). In comparison, the sand showed lower basal respiration rates overall than the loam. On the other hand, PAA reduced the basal respiration in the sand directly after addition (measurement point 0), from 1.6 ± 0.1 without PAA to 1.14 ± 0.03 µg CO 2 -C g⁻¹ soil h⁻¹ at the highest PAA concentration (-30 ± 2%). Interestingly, PAA increased the basal respiration in the loam, from 5.6 ± 0.3 without PAA to 9.1 ± 0.7 µg CO 2 -C g⁻¹ soil h⁻¹ at the highest PAA concentration (+ 62 ± 6%). However, the effect of PAA disappeared within the first three incubation weeks and was no longer significantly different after measurement point 3. Soil moisture regimes showed no significant effects on the basal respiration of both soils investigated, neither alone nor in combination with PAA. Figure 3 In both soils, total substrate-induced respiration (SIR tot ) significantly increased over time with the loam showing overall higher respiration rates than the sand (Fig. 3 b and Table 4 in SI). Mean SIR tot in the sand increased for all PAA concentrations and soil moisture regimes, from 1.51 ± 0.03 at measurement point 0 to 2.15 ± 0.04 µg CO 2 -C g − 1 soil h − 1 at measurement point 10. Mean SIR tot in the loam increased from 3.6 ± 0.2 at measurement point 0 to 5.5 ± 0.4 µg CO 2 -C g − 1 soil h − 1 at measurement point 10. In both soils, the observed fluctuations in SIR tot were predominantly attributed to changes in substrate-specific microbial responses rather than alterations in baseline microbial activity. This is evidenced by the relatively constant basal respiration across treatments, contrasting with the more pronounced and variable changes in SIR patterns (Fig. 3 c). For the sand, basal and substrate-induced respiration rates increased for all substrate groups (carbohydrates, amines, and carboxylic acids) over time, with incubation time being the most significant factor explaining the variability (ω² = 0.87, p < 0.0001, df = 3) (Fig. 4 ). PAA significantly increased basal respiration (ω² = 0.03, p < 0.0001, df = 3), while it reduced SIR for carbohydrates (ω² = 0.11, p < 0.0001, df = 3), amines (ω² = 0.13, p < 0.0001, df = 3) and carboxylic acids (ω² = 0.14, p < 0.0001, df = 3). These effects remained consistent throughout the incubation time. Compared to the untreated control, SIR reductions at the highest PAA concentration were 90%, 54%, 100%, and 52% at measurement points 0, 3, 5, and 10, respectively. Thus, the highest PAA concentration led to complete SIR suppression, particularly at measurement points 0 and 5. At the end of the incubation time, soil samples subjected to drying-rewetting cycles exhibited higher basal respiration rates (+ 7.28 ± 0.09%) than under static moisture conditions. Conversely, for all SIR groups, static soil moisture induced higher respiration rates than drying-rewetting cycles at PAA concentration up to 250 mg Kg -1 soil (+ 85 ± 12%). At the highest PAA concentration, however, the two soil moisture regimes showed no significant differences anymore. Figure 4 The SIR variation coefficients underscored these findings as they increased over time (ω² = 0.12, p < 0.0001, df = 3) but decreased with higher PAA concentrations (ω² = 0.14, p < 0.0001, df = 3), nearly dropping to zero during the initial weeks of incubation (Fig. 3 c). Comparable to the sand, both basal and substrate-induced respiration rates of the loam increased over time and for all substrate groups. However, in contrast to the sand, the basal respiration increased only at low PAA concentrations (ω² = 0.08, p < 0.0001, df = 3), while the highest PAA concentration significantly reduced basal respiration. Comparing the control and the highest PAA concentration, the overall basal respiration decreased by 7.0 ± 0.3% at the beginning of the incubation for the SIR of carbohydrates, amines, and carboxylic acids. Interestingly, the effect of PAA addition on SIR was less consistent in the loam compared to the sand, with the two moisture regimes showing opposite responses: under drying-rewetting cycles, SIR respiration increased with increasing PAA concentration, whereas SIR respiration in static soil moisture decreased. Comparing the control and the highest PAA concentration, the overall SIR of the loam under static soil moisture conditions was reduced by 75 ± 1% after 10 weeks. Here, the highest respiration suppression of 83 ± 15% was observed for carbohydrates (4.3 ± 0.5 to 0.7 ± 0.1 µg CO 2 -C g -1 soil h -1 ). Although less pronounced, the same pattern was observed for amines and carboxylic acids. From measurement point 5 on, the loam incubated at static moisture conditions consistently showed higher basal respiration rates compared to the respective samples subjected to drying-rewetting cycles. Also, the SIR rates were consistently higher from measurement point 3 onward at static soil moisture conditions than at drying-rewetting cycles. After 10 weeks, the loam incubated under static moisture conditions exhibited a 12.2 ± 0.1% increase in basal respiration and a 487 ± 62% increase in SIR when either untreated or treated with low PAA concentrations (up to 250 mg PAA Kg -1 soil). As with the sand, the differences in loam decreased with increasing PAA concentration and for soil moisture regimes, with no significant differences anymore at the highest PAA concentration. The SIR variation coefficient for the loam further supports these findings, showing a significant increase over time (ω² = 0.15, p < 0.0001, df = 3). While PAA concentration (ω² = 0.02, p = 0.0005, df = 3) still slightly contributed to the variation, its effect was less pronounced than in the sand. In contrast, the sample type (ω² = 0.06, p < 0.0001, df = 1) had a stronger influence on the variation in the loam, particularly towards the end of incubation, as demonstrated by its significant interaction with the incubation time (ω² = 0.07, p < 0.0001, df = 3). Relationships between the parameters investigated For the sand, PCA indicated that the first two principal components explained 82.5% of the total variance, with PC1 accounting for 58.1% and PC2 for 24.4% (Fig. 5 a- 1 ). PC1 was primarily influenced by SIR variables, including carboxylic acids, amines, and carbohydrates. PC2 was dominated by WHC max and soil pH. A negative correlation was observed between soil pH and WHC max . SIR variables were positively correlated with each other and showed no correlation with WHC max or soil pH. Figure 5 The PCA biplot (Fig. 5 a- 2 ) revealed no distinct clustering based on the two soil moisture regimes: drying-rewetting cycles tended towards higher soil pH values, while static soil moisture conditions displayed a broader distribution along PC1 with higher respiration rates. Clustering based on PAA concentration (Fig. 5 a- 3 ) was more pronounced along PC2, where higher PAA concentrations were associated with increased WHC max and lower soil pH values. Basal respiration rates did not show any clear clustering patterns between incubation conditions or substrate groups. However, for the SIR variables, the highest PAA concentration corresponded to the lowest respiration rates compared to the lower PAA concentrations and the control. The most distinct separation of samples was based on the measurement points, with measurement point 10 clearly separated from earlier points, indicating higher respiration rates along PC1 (Fig. 5 a- 4 ). For the loam, Fig. 5 b- 1 indicated that the first two principal components explained 76.4% of the total variance, with PC1 accounting for 58.0% and PC2 for 18.3%. Similar to the sand, PC1 was dominated by SIR variables, while PC2 by WHC max and soil pH. Again, soil pH was negatively correlated with WHC max , and the SIR variables were positively correlated with each other, showing no distinct relationship with WHC max or soil pH. The PCA biplot (Fig. 5 b- 2 ) revealed distinct clustering based on the soil moisture regimes: soil samples subjected to drying-rewetting cycles tended to higher soil pH values, while static soil moisture conditions exhibited a broader distribution along PC1, with notably higher respiration rates. Clustering based on PAA concentration was apparent along PC2 (Fig. 5 b- 3 ), with higher PAA concentrations associated with increased WHC max and reduced soil pH. At the highest PAA concentration, both basal respiration and SIR exhibited lower respiration rates and a narrower distribution along PC1 compared to the control and lower PAA concentrations. Clustering by measurement points (Fig. 5 b- 4 ) was distinct, with measurement point 10 clearly separated from earlier points, reflecting higher respiration rates along PC1. Over time, the cluster distribution shifted from a wider spread along PC2 to a broader distribution along PC1. This indicates that the influence of PAA concentration on soil pH and WHC max of the loam diminished over time. Scanning electron microscopy Although the SEM images did not show noticeable differences based on measurement point or soil moisture regimes for both soils, they clearly showed membranous PAA structures between the soil particles, forming particle coatings as well as interparticulate bridges and connections of varying sizes (Fig. 6 ). At higher magnification, the bridging and coating effects of PAA became even more evident, revealing that the PAA membrane network not only bonded soil particles but also organic material. Figure 6 Discussion This study examined the impact of PAA on maximum water holding capacity (WHC max ) and soil pH, and how these changes affected soil microbial activity in a sand and loam under different moisture conditions. PAA increased WHC max in both soils, with loam revealing higher WHC max under drying-rewetting cycles. PAA decreased soil pH in both soils, with a stronger reduction in the sand, where it remained significant throughout the incubation time. Basal respiration decreased in the sand with increasing PAA concentration, while it increased in the loam, especially at low PAA concentrations. Substrate-induced respiration (SIR) was suppressed in both soils, particularly in sand at high PAA concentrations, and even stronger under static moisture conditions. All in all, the effect of PAA on SIR varied with moisture regime, decreasing under static moisture conditions and increasing under drying-rewetting cycles at relatively lower PAA concentrations. As hypothesized, PAA significantly increased WHC max in both investigated soils. This is in line with various other studies investigating the effect of SAPs on soil WHC max , although the effect size partly differed considerably [ 32 – 34 ]. For example, [ 34 ] investigated four crosslinked acrylamide and acrylic acid polymers in a sandy soil with similar grain size distribution, CEC, and C org , but different application types (powder vs. granules of up to 2 mm). The four polymers applied at a concentration of 2500 mg Kg − 1 soil increased the water content of the sandy soil by roughly 65%, corresponding to a PAA absorption capacity of roughly 90 mL water g − 1 polymer. In this study, the PAA powder only absorbed 22 mL water g − 1 in the sand. This finding highlights the influence of the application type on the efficiency of PAA to improve water retention in soil: the relatively lower surface area of PAA granules compared to powder allows for the creation of a more stable, local hydrogel network, which can counteract the confining pressure and suction tension of the soil matrix effectively [ 35 , 36 ]. In contrast, PAA powder provides a relatively high surface area, which promotes strong and fast interactions with soil particles, e.g., in terms of their adsorption, typically reducing their swelling potential [ 5 ]. Furthermore, dispersion effects of PAA polymer when homogeneously mixed into the soil might prevent the formation of a strong, spatially interconnected network that can withstand the confining pressure of the soil matrix and efficiently absorb water from its surroundings [ 27 , 37 ]. Interestingly, the positive effect of PAA on the WHC max of both investigated soils was not completely reduced over time or with increased drying-rewetting cycles. Even after 10 drying-rewetting cycles, the PAA-induced WHC max remained relatively stable for the sand and showed a linear increase with increasing PAA concentration, suggesting a concentration-independent behavior. This contrasts [ 38 ] who reported a reduced water absorbance of SAPs in ultrapure water, tap water, and soil extracts with increasing drying-rewetting events. They also noted that the extent of the functional loss was related to the severity of the drying events. Despite fully drying the soils in this study during the respective drying-rewetting cycles, representing such typical severe drying events, no decline in water retention was observed after rewetting. While PAA retained its functionality in the sand under both moisture regimes, the situation was different in the loam: here PAA lost its functionality completely over time and, in addition to the loss of additional PAA-induced water uptake, the WHC max was even lower compared to the control. In this context, freely swollen PAA in the respective soil solutions also showed a significantly lower swelling capacity compared to demineralized water, especially when swollen in the loam soil solution. These effects are likely due to cation-mediated crosslinking between PAA polymer chains, solution salinity and pH effects that restrict hydrogel network expansion and water absorption into the three-dimensional PAA hydrogel network [ 7 , 8 , 16 ]. Especially the ionic strength in the soil solutions reduces the osmotic pressure difference between PAA and the solvent, whereas low solution pH promotes cation release and consequently PAA crosslinkage and PAA-mineral interactions in soil [ 39 , 40 ]. The results showed that the initial PAA treatment lowered the soil pH in both soils, most likely due to the dissociation of carboxylic acid groups releasing hydrogen ions [ 41 ]. This effect persisted in the sand but disappeared in the loam after one week. Here, favorable pH buffer conditions in terms of higher CEC and C org in the loam (three times that of sand) might have stabilized the soil pH, e.g., through functional groups in OM or exchange at clay mineral surfaces [ 42 ]. Under static conditions, PAA completely lost its positive effects on the WHC max of the loam after 10 weeks and even reduced it compared to the untreated control, likely because the nearly neutral solution in loam under drying-rewetting conditions and the acidic conditions in the sand resulted in comparable ionic strength and crosslinking environments. On the one hand, static moisture conditions likely promoted cation release into the soil solution, enabling ionic crosslinking of PAA polymer chains and polymer-clay interactions [ 43 , 44 ]. On the other hand, the physical limitation of soil particles and water competition with other reactive soil components such as SOM and clay particles also limited PAA swelling [ 27 , 45 – 47 ]. Existing studies have demonstrated that water redistribution in the soil matrix occurs as a function of capillary forces and the spatio-temporal (re)wetting of mineral surfaces. This process is followed by the gradual dehydration of the interparticulate SAP hydrogel over time, reaching an equilibrium state between the spatially condensed interparticle gel network and the surrounding soil matrix [ 27 , 37 ]. Further, the relatively lower pH environment in the loam may have further promoted the availability of cations by successively releasing them from cation exchangers under static moisture conditions, which further enhanced the crosslinking effect between the PAA polymer chains themselves and the cementation in the interparticle space via polymer-clay interactions and successive dehydration [ 6 ]. While the soils subjected to drying-rewetting cycles experienced only three days of moist conditions before the next drying event, the static samples had a continuous period for these processes to progress without interruption. Thus, the dynamic nature of the drying-rewetting cycles likely interrupted striking processes and thereby prevented irreversible PAA dehydration in the interparticle space. However, [ 48 ] immersed different hydrogels in solutions containing varying concentrations of divalent ions such as Cu(II) and Zn(II) and measured their swelling degrees after two hours. Besides demonstrating a significant reduction in hydrogel swelling with increasing ion concentrations, the authors showed that crosslinking processes occur relatively quickly. This indicated that the disruption of PAA hydrogel crosslinking due to drying-rewetting cycles were not the driving factor in the investigated loam. In addition, increased aeration while drying lead to a reduction in CO 2 concentration, raising the soil pH and mitigating the pH-reducing effects of PAA via reducing carbonic acid formation and lowering hydrogen ion concentrations [ 49 – 52 ]. The higher pH, combined with changes in ionic strength due to the drying-rewetting process, likely helped preserve the swelling ability of PAA in the soil interparticle space. This emphasizes the need for future studies to investigate the role of drying-rewetting cycles of different durations, including partial drying events to deepen the understanding of the underlying mechanisms and their impact on the performance of hydrogels under real conditions. In addition, monitoring the ionic strength and concentration of potential PAA crosslinking ions during drying-rewetting cycles would provide further important insights into the relevance of changing chemical soil solution properties. The measured basal respiration for both soils were within the range reported in other studies, with a tendency for higher respiration rates observed under static moisture conditions compared to drying-rewetting conditions [ 53 – 56 ]. Repeated drying-rewetting cycles typically impose osmotic and oxidative stress on microbial communities, leading to cell lysis, which reduces microbial biomass, shifts in microbial energy use, as microbes divert resources toward stress recovery mechanisms, such as repairing cell membranes or producing osmolytes, rather than towards respiration [ 57 – 59 ]. This stress also tends to reduce microbial diversity, with stress-tolerant microbes becoming more dominant. Conversely, in static moisture treatments, microbial communities experience fewer disruptions, allowing them to maintain a more stable environment [ 60 , 61 ]. This stability enables higher metabolic activity and basal respiration rates, as microbes can focus more energy on growth and maintenance rather than stress recovery. Thus, the differences in respiration rates between static and cyclic moisture conditions reflect the broader impacts of moisture fluctuations on microbial community dynamics and function. Concerning the differences in basal respiration as function of the two soil types, the loam consistently showed higher microbial respiration rates than the sand, which aligns with existing literature linking basic soil physicochemical properties such as soil pH, soil carbon content and soil water availability to soil respiration [ 62 , 63 ]. One key factor explaining the differences in microbial respiration between the soils is the pH, a well-established determinant of microbial activity and community composition. [ 21 ] identified a critical threshold at pH 5.5, below which microbial carbon use efficiency and respiration tend to decline. While the loam consistently maintained pH values above this threshold across all PAA concentrations, the sand exhibited lower pH values, likely contributing to its generally reduced respiration rates. This could also explain the relatively lower SIR response to added carbon sources in the sand compared to the loam, respectively. In line with [ 21 ], the results suggest that the microbial community in the loam exhibited a higher capacity to decompose the added substrates, whereas the microbial community in the sand was less responsive to changes in resource availability. [ 64 ] found similar results, observing a stronger increase in respiration with rising carbon content in a clay loam compared to a loamy sand. Although PAA significantly affected soil microbial respiration in a concentration-dependent manner, the results suggest that respiration patterns cannot be solely attributed to PAA. Instead, they likely reflect complex interactions with other factors, including soil pH, WHC max , incubation time, and moisture dynamics. Contrary to our expectations and current scientific knowledge, PAA showed no clear drought-mitigating effect in the two investigated soils. Further, it did not lose its effects on soil microbial respiration over time or due to moisture dynamics. Depending on the concentration, PAA reduced soil microbial respiration in both soils and shifted substrate usage patterns, indicating a lower capacity to utilize added carbon sources for the respective microbial communities. Since PAA is well-known to be mostly non-biodegradable [ 9 ], the effects on soil microbial activity are mainly not attributed to the utilization of PAA-derived carbon. In nature and as shown by SIR, the reduced utilization of easily degradable carbohydrates at high PAA concentrations suggests enzyme inhibition, such as of amylases, likely due to a decreased abundance of carbohydrate-utilizing microbes. For more complex substrates like amines and carboxylic acids, which require specialized metabolic pathways (e.g., deamination for amines and beta-oxidation for carboxylic acids), the reduced utilization at high PAA concentrations suggests similar inhibitory effects. These may include the induction of oxidative stress and pH shifts, which suppress microbial metabolism, as it has been shown for other polymers such as polyethylene and polylactic acid [ 65 , 66 ]. Respective changes could lead to a shift in microbial community structure, favoring microbes that metabolize simpler substrates over those capable of degrading more complex compounds. Further, changes in soil pH might have directly influenced soil microbial activity, as certain microbial groups are more adapted to pH ranges or resilient to pH changes. Thus, pH shifts might favor or inhibit acidophilic or alkaliphilic microorganisms, potentially disrupting the overall balance of the soil microbial community and impairing their ability to process organic matter [ 67 – 69 ]. Soil moisture conditions also contributed to the PAA-induced effects on soil microbial respiration, as both excessive and insufficient moisture levels can reduce respiration rates: High water content can limit oxygen availability by filling pore spaces and consequently restricting aerobic microbial processes [ 70 ]. Here, SAPs, like PAA, may promote this effect by further occupying the available soil pore spaces during their swelling, thereby reducing soil permeability and pore interconnectivity [ 71 ], a phenomenon also observed for natural compounds, such as bacterial polysaccharides and EPS [ 72 ]. Conversely, limited water availability can inhibit soil microbial respiration by reducing substrate and nutrient accessibility and causing cytoplasmic dehydration in soil organisms [ 73 ]. While SAPs have been shown to increase overall soil water content [ 24 ], the relative proportion of water available to the soil microbial community may decrease, exacerbating the respiration-limiting effects associated with low water availability [ 4 ]. In the sand, both moisture regimes had a consistent negative effect on PAA-induced soil respiration, whereas this negative effect was only observed under static moisture conditions in the loam. This can be attributed to their differences in soil texture, water retention capacity, and microbial community responses. In general, soil moisture fluctuations induced by drying-rewetting events can create osmotic and oxygen stress that can damage microbial cells and reduce microbial biomass [ 74 ]. Additional PAA exposure under these fluctuating conditions might exacerbate those stresses and consequently further reduce soil respiration. On the one hand, sands, with their low water-holding capacity, face limited moisture availability under both static and drying-rewetting conditions [ 75 ]. Together with the PAA-induced water competition and oxidative stress, it further restricts soil microbial activity and respiration. On the other hand, loams can retain more water, which might allow microbes to recover more effectively during drying-rewetting cycles, partly mitigating the negative impact of PAA. Furthermore, soil drying, along with interparticulate PAA dehydration and soil pore aeration, could improve oxygen availability and reduce oxidative stress caused by PAA. Both [ 8 ] and [ 4 ] demonstrated that the addition of SAP reduces water evaporation rates during drying events, leading to higher soil water content over an extended period. This effect could mitigate drought stress by maintaining suitable conditions for soil microbes, thereby supporting higher microbial respiration for a longer duration. In the sand, enhanced aeration from drying-rewetting cycles may not have been sufficient to counteract the negative impacts of PAA, as sand typically has better aeration properties. Therefore, differences in aeration between constant and drying-rewetting conditions might be smaller in the sand compared to the loam. At this point, it is important to note that the complex interactions and mechanisms proposed have not been explored in detail yet. Thus, the initial insights from this study suggest potential relationships between PAA exposure, soil respiration, and microbial activity, highlighting the need for further systematic research. Besides soil pH, WHC max , and soil moisture, other soil-specific physicochemical properties and processes, as influenced by PAA, should also be considered, e.g., soil aggregation, pore structure recreation, and the potential formation of solid SAP residues: On the one hand, PAA is well-known to alter soil aggregation and to spatio-temporal redistribute soil micro- and macroaggregates, playing a crucial role in defining microhabitats, moisture availability, and soil aeration [ 15 , 76 , 77 ]. Changes in soil porosity and soil pore structures can alter water and air movement, potentially leading to respective limitations that further suppress microbial activity. For example, larger aggregate sizes, as promoted by PAA, are generally associated with lower respiration rates and higher fungi-to-bacteria ratios compared to smaller ones [ 78 , 79 ]. On the other hand, interparticulate PAA hydrogel might form solid residues over time or upon drying-rewetting, which could further reduce soil pore interconnectivity due to their cemented solid structures over larger interparticle areas. However, the extent, duration and relevance of this process is still poorly understood and is currently the focus of research [ 6 ]. Although our study provided valuable first insights into the effect of PAA on soil microbial activity and substrate utilization, there are several areas that should be further exploration and investigation to deepen our understanding: one key but typical limitation is the limited diversity of substrates used in studies, which may not fully reflect the range of OM utilized by soil microbes. Thus, including a broader variety of substrates could provide a more comprehensive view of microbial processes under PAA exposure. Additionally, while shifts in microbial community composition are suggested, detailed profiling of microbial groups and their functional pathways is still lacking, which could be addressed using advanced molecular techniques, such as metagenomics [ 80 ]. Although two soils have been investigated in this study, the variability in soil types and long-term effects of PAA exposure also remain underexplored, highlighting the need to conduct systematic studies with different soil types and implementing long-term exposure assessments. Furthermore, environmental factors potentially interacting with PAA-induced changes in soil (e.g., pH shifts and oxidative stress) need more attention in multi-stressor studies. Finally, the exact mechanisms behind the ecotoxicological impact of PAA on soil microbiology, such as enzyme inhibition or oxidative stress, require further targeted biochemical investigations [ 81 ]. Conclusion This study demonstrates that PAA significantly alters WHC max and soil pH, with subsequent effects on soil microbial activity as function of concentration, soil type and moisture dynamics. PAA increased WHC max in both sand and loam by absorbing available water into its three-dimensional interparticulate hydrogel network, but its effect intensity and duration varied, persisting in sand while declining in loam due to ionic crosslinking and pH-buffering effects. PAA further reduced soil pH, particularly in the sand, which remained acidic throughout the incubation period, while the loam exhibited a transient pH decrease. Concerning the effect of PAA on soil microbial activity, low PAA concentrations seem to temporarily stimulate soil respiration, e.g. by facilitating water and nutrient uptake and causing temporary positive stress due to short-term pH changes in soil. However, at higher concentrations, PAA tends to exert inhibitory effects, probably through oxidative stress, enzyme inhibition, or microbial community shifts. The observed suppression of substrate-induced respiration (SIR), especially for more complex substrates such as amines and carboxylic acids, indicates that PAA impairs microbial functional diversity and thus potentially also the entire biochemical cycle in soil. The strong interactions between PAA-induced effects and soil moisture conditions highlight its role in modulating microbial activity: while static moisture conditions increased PAA-induced suppression, drying-rewetting cycles mitigated some negative effects but also introduced additional stress, probably through osmotic fluctuations, oxidative stress, and enzyme disruption. Furthermore, PAA seems to indirectly affect soil microbial activity by modulating soil physical properties, such as soil porosity, or forming solid SAP residues and should be further investigated. All in all, this study highlights the importance of considering both chemical and physical stressors when assessing the application of PAA as soil amendment and its effect on soil microbiology. Since the soil type modulated the magnitude of PAA-induced effects and given the widespread use of SAPs in agriculture and land management, a more comprehensive understanding of their long-term effects on soil microbial communities, nutrient cycling, and ecosystem stability is critical. Thus, future should investigate soil microbial adaptation mechanisms, the persistence of PAA in soil, and potential mitigation strategies to balance the benefits of SAPs with their environmental impact on soil health and ecosystem functioning. Declarations Competing Interests: The authors declare no competing interests Financial support This research was financially supported by the Deutsche Forschungsgemeinschaft (Grant No. BU 3763/1–1). Author Contribution Conceptualization: C.B., Z.S., S.R., and J.N.; Methodology and experimental setup: C.B., Z.S., S.R., and J.N.; Material preparation and data collection: S.R.; Data evaluation and interpretation: S.R., C.B., and Z.S.; Writing - original draft preparation: S.R. and C.B.; Writing - review and editing: S.R., Z.S., J.N., and C.B.; Funding acquisition: C.B.; Project management: C.B.; Supervision: C.B. and Z.S. Acknowledgement We kindly thank Gabriele E. Schaumann for her valuable feedback on the manuscript Data Availability The data that supports the findings of this study are available from the corresponding author upon reasonable request. References Venkatachalam, D. & Kaliappa, S. Superabsorbent polymers: a state-of-art review on their classification, synthesis, physicochemical properties, and applications. Rev. Chem. Eng. 39 , 127–171. https://doi.org/10.1515/revce-2020-0102 (2023). Zohuriaan-Mehr, M. J. & Kabiri, K. SUPERABSORBENT POLYMER MATERIALS: A REVIEW (2008). 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The Characteristics of Time-Dependent Changes of Coefficient of Permeability for Superabsorbent Polymer-Soil Mixtures. Materials 15 , 4465. https://doi.org/10.3390/ma15134465 (2022). Mitchell, R. & Nevo, Z. Effect of Bacterial Polysaccharide Accumulation on Infiltration of Water Through Sand. Appl. Microbiol. 12 , 219–223. https://doi.org/10.1128/am.12.3.219-223.1964 (1964). Stark, J. M. & Firestone, M. K. Mechanisms for soil moisture effects on activity of nitrifying bacteria. Appl. Environ. Microbiol. 61 , 218–221. https://doi.org/10.1128/aem.61.1.218-221.1995 (1995). Bian, H. et al. Soil Moisture Affects the Rapid Response of Microbes to Labile Organic C Addition. Front. Ecol. Evol. 10 , 857185. https://doi.org/10.3389/fevo.2022.857185 (2022). Gutierrez, M. M. et al. Investigating a microbial approach to water conservation: Effects of Bacillus subtilis and Surfactin on evaporation dynamics in loam and sandy loam soils. Front. Sustain. Food Syst. 6 , 959591. https://doi.org/10.3389/fsufs.2022.959591 (2022). Salih, S. M. & Al Abaied, A. I. Effect of Super Absorbent Polymer and Ceratophyllum Powder Application on Some Soil Physical Properties. IOP Conf. Ser. Earth Environ. Sci. 1222 , 012030. https://doi.org/10.1088/1755-1315/1222/1/012030 (2023). Yang, Y. et al. Effects of long-term super absorbent polymer and organic manure on soil structure and organic carbon distribution in different soil layers. Soil. Tillage Res. 206 , 104781. https://doi.org/10.1016/j.still.2020.104781 (2021). Liao, H. et al. Contrasting responses of bacterial and fungal communities to aggregate-size fractions and long-term fertilizations in soils of northeastern China. Sci. Total Environ. 635 , 784–792. https://doi.org/10.1016/j.scitotenv.2018.04.168 (2018). Sun, D. et al. Microbial communities in soil macro-aggregates with less connected networks respire less across successional and geographic gradients. Eur. J. Soil. Biol. 108 , 103378. https://doi.org/10.1016/j.ejsobi.2021.103378 (2022). Lahlali, R. et al. High-throughput molecular technologies for unraveling the mystery of soil microbial community: challenges and future prospects. Heliyon 7 , e08142. https://doi.org/10.1016/j.heliyon.2021.e08142 (2021). Dell’Ambrogio, G., Wong, J. W. Y. & Ferrari, B. J. D. Ecotoxicological effects of polyacrylate, acrylic acid, polyacrylamide and acrylamide on soil and water organisms (Swiss Centre for Applied Ecotoxicology, 2019). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6225306","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":433807670,"identity":"df6a5c93-6ffc-4c9c-b602-450939208643","order_by":0,"name":"Christian Buchmann","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYFACHgYGxgYQg/kAROAA8VrYEhgYEkjTwmNAnBb+Bt5jEj93bJM3l+759rnwx2EGvuMN+LVIHOBLk+w9c9tw55yzm2fPSDjMIHmGgDUGDDxm0oxttxk33MjdzMwD1GJwI4E4LfYbbuQ8hmi5/4A4LYlALcxQW/DrYJA4zJds2dt2O3nDjTRj5hlp6TySZwg4jL+99+CNn223bTfcSH7MXGBjLcd3/AABa5jR2DwE1OPRPgpGwSgYBaMADgAOmURLrXPKTQAAAABJRU5ErkJggg==","orcid":"","institution":"Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau","correspondingAuthor":true,"prefix":"","firstName":"Christian","middleName":"","lastName":"Buchmann","suffix":""},{"id":433807671,"identity":"d8b03291-faac-42a8-b133-4f2f792efb38","order_by":1,"name":"Simon Rudolph","email":"","orcid":"","institution":"Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau","correspondingAuthor":false,"prefix":"","firstName":"Simon","middleName":"","lastName":"Rudolph","suffix":""},{"id":433807672,"identity":"9540a649-a396-407d-a0b0-02cdf246ade1","order_by":2,"name":"Janina Neff","email":"","orcid":"","institution":"Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau","correspondingAuthor":false,"prefix":"","firstName":"Janina","middleName":"","lastName":"Neff","suffix":""},{"id":433807674,"identity":"f7138ae3-33c1-4560-ad19-258e98278199","order_by":3,"name":"Zacharias Steinmetz","email":"","orcid":"","institution":"Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau","correspondingAuthor":false,"prefix":"","firstName":"Zacharias","middleName":"","lastName":"Steinmetz","suffix":""}],"badges":[],"createdAt":"2025-03-14 10:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6225306/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6225306/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-04457-8","type":"published","date":"2025-06-03T15:57:22+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79299863,"identity":"5fe6e2c2-33a4-4277-baf4-bad52534f4a7","added_by":"auto","created_at":"2025-03-26 18:35:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1040316,"visible":true,"origin":"","legend":"\u003cp\u003eMaximum water holding capacity (WHC\u003csub\u003emax\u003c/sub\u003e) as function of PAA concentration (0 - 2500 mg Kg\u003csup\u003e-1\u003c/sup\u003e dry soil) and measurement point for (a) sand (Lufa 2.1) and (b) loam (Lufa 2.4). Numbers in the grey boxes denote the measurement point (incubation week/drying-rewetting cycle) for the static (blue bars) and cyclic soil samples (red bars), respectively. Error bars represent standard errors.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6225306/v1/7186872a808017e2683d2ce3.png"},{"id":79299780,"identity":"9177034f-b7ca-4a67-bd32-2da65a150081","added_by":"auto","created_at":"2025-03-26 18:27:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1337639,"visible":true,"origin":"","legend":"\u003cp\u003eSoil pH as function of PAA concentration (0 - 2500 mg Kg\u003csup\u003e-1\u003c/sup\u003e dry soil) and measurement point for (a) sand (Lufa 2.1) and (b) loam (Lufa 2.4). Numbers in grey boxes denote the measurement point (incubation week/drying-rewetting cycle) for the static (blue line) and cyclic soil samples (red line), respectively. Error bars represent standard errors.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6225306/v1/06978c5601f113973831ca6c.png"},{"id":79299779,"identity":"25cd8283-3644-491b-9e05-531281510976","added_by":"auto","created_at":"2025-03-26 18:27:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1433630,"visible":true,"origin":"","legend":"\u003cp\u003ea) Basal respiration for sand (Lufa 2.1) and loam (Lufa 2.4), b) total substrate induced respiration (SIR\u003csub\u003etot\u003c/sub\u003e), and c) SIR\u003csub\u003etot \u003c/sub\u003evariation coefficient as a function of PAA concentration (0 - 2500 mg Kg\u003csup\u003e-1\u003c/sup\u003e dry soil) and measurement point (incubation week/drying-rewetting cycle). Numbers in grey boxes denote the measurement point (incubation week/drying-rewetting cycle) for the static (blue line/bars) and cyclic soil samples (red line/bars), respectively. For SIR measurement, black-bordered bar areas represent basal respiration, grey-bordered areas indicate SIR fractions of SIR\u003csub\u003etot\u003c/sub\u003e. Error bars represent standard errors.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6225306/v1/2f9e3ae6e3bc95374348ae91.png"},{"id":79299864,"identity":"e7d15f6d-0cad-415b-943d-c3fc9308d20a","added_by":"auto","created_at":"2025-03-26 18:35:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5834533,"visible":true,"origin":"","legend":"\u003cp\u003eBasal and substrate-induced respiration (SIR) for sand (Lufa 2.1) and loam (Lufa 2.4) as a function of PAA concentration (0 - 2500 mg Kg\u003csup\u003e-1\u003c/sup\u003e dry soil) and measurement points (incubation week/drying-rewetting cycle) for the static (blue line) and cyclic soil samples (red line). Error bars represent standard errors.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6225306/v1/01a5d26911c59371e75cc79d.png"},{"id":79299865,"identity":"88d74e81-b0f6-4e93-99a4-9eadbcbc478d","added_by":"auto","created_at":"2025-03-26 18:35:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":6039752,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) of the investigated parameters for sand\u0026nbsp;(Lufa 2.1) and loam (Lufa 2.4) with (a) contribution of variables to PC1 and PC2, and biplots showing sample clustering by (b) soil moisture conditions (drying-rewetting cycles (c) and static moisture conditions (s)), (c) PAA concentration (0 - 2500 mg Kg\u003csup\u003e-1\u003c/sup\u003e dry soil), and (d) measurement points (MP).\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6225306/v1/9ca7cfbd893a2af06a70719b.png"},{"id":79299788,"identity":"ddd1f52d-122f-4ae8-83db-fde27f9553b7","added_by":"auto","created_at":"2025-03-26 18:27:08","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":14544290,"visible":true,"origin":"","legend":"\u003cp\u003eScanning Electron Microscopy (SEM) images of sand (Lufa 2.1) and loam (Lufa 2.4), either untreated or PAA-treated (2500 mg Kg\u003csup\u003e-1\u003c/sup\u003e dry soil). Arrows highlight dehydrated PAA hydrogel structures bridging between soil particles or OM structures.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-6225306/v1/6779ba71871ebae888837763.png"},{"id":84242700,"identity":"1b9e0b7d-b680-4468-8dcf-e75c83de37fa","added_by":"auto","created_at":"2025-06-09 16:11:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":29742299,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6225306/v1/dcc9e37f-99f8-4604-a712-494e50f49e07.pdf"},{"id":79299777,"identity":"c7b09969-1a26-4fbd-bdae-ed08a159bbb1","added_by":"auto","created_at":"2025-03-26 18:27:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":43928,"visible":true,"origin":"","legend":"","description":"","filename":"TablesSI.docx","url":"https://assets-eu.researchsquare.com/files/rs-6225306/v1/9805f52dc706e627f8620cf8.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of polyacrylic acid as soil amendment on soil microbial activity under different moisture regimes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSuperabsorbent polymers (SAPs) can absorb and retain large amounts of water or aqueous solutions, which makes them commonly used as soil conditioners to alter soil properties, such as the maximum water holding capacity (WHC\u003csub\u003emax\u003c/sub\u003e), soil structural stability, as well as the availability of nutrients, fertilizers, and pesticides [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Based on their properties and synthesis methods, SAPs can be categorized by their origin (natural, synthetic, or hybrid) and crosslinking type (chemical or physical bonds) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In this context, polyacrylic acid (PAA) is one of the most frequently used synthetic SAPs due to its high water absorption (swelling) capacity, typically ranging between 300\u0026ndash;500 g water g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e dry polymer [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, the water absorption capacity of SAPs can be significantly impaired by the presence of certain ions, particularly multivalent cations (e.g., Ca\u0026sup2;⁺, Al\u0026sup3;⁺), through cation-mediated crosslinking [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This process occurs when multivalent cations interact with anionic groups on the polymer chains, forming additional crosslinks within the network structure and resulting in reduced water absorption capacity and altered key physicochemical properties, including mechanical strength, diffusion rates, and pH sensitivity [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile the beneficial properties of superabsorbent polymers (SAPs) are well-documented, their introduction into soil systems may pose several risks and challenges. A major concern is the persistence of PAA due to its extremely low biodegradation rates of only 0.2\u0026ndash;0.5% y\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in soil [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In contrast to naturally occurring SAPs such as gellan, alginate, or mucilage, this persistence raises the potential for long-term accumulation, with reported concentrations reaching up to 10 g SAP Kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Moreover, it has been shown that the positive effects of SAPs on soil WHC can diminish within three months after application, necessitating frequent reapplications to maintain effectiveness in arid and semi-arid soils and thereby further increasing concerns about the accumulation and impact of PAA in soil [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Additionally, soil moisture dynamics, such as regular drying-rewetting cycles, can significantly alter the functionality of SAPs, e.g., leading to reduced water absorption capacity over time [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Aging processes, including chemical, photolytic, and mechanical transformation and degradation, might further contribute to the potential fragmentation of PAA into smaller particles. These fragments can get into deeper soil layers or into neighboring ecosystems with potential negative effects on the environment [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile PAA is well-recognized for its beneficial impacts on various soil physicochemical properties, the consequences of its persistence, accumulation, and aging on soil microbial activity remain largely unknown [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Given the essential role of soil microbial activity in nutrient cycling, organic matter decomposition, and overall soil health [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], it is crucial to consider how synthetic SAPs such as PAA might affect, e.g., soil microbial diversity, metabolic functioning, and respiration dynamics to better understand the long-term implications on soil ecosystems. On the one hand, PAA may disrupt or alter microbial processes by altering soil structure and porosity [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], which potentially affects the availability of microbial habitats, water distribution, and oxygen diffusion throughout the soil. On the other hand, the chemical properties of PAA, particularly its capability to form complexes with essential nutrients, its presence as a carbon source, and its potential influence on soil pH might also affect the microbial growth and their metabolic activity [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Thus, its persistence and accumulation potential could make PAA a long-term stressor to microbial communities, altering their functional capabilities and community dynamics through adaptive responses over time.\u003c/p\u003e \u003cp\u003eSoil microbial respiration can be divided into autotrophic respiration from plant roots and associated microbes using self-produced energy and heterotrophic respiration from soil microbes decomposing organic matter (OM) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Since heterotrophic respiration is heavily influenced by environmental factors such as soil moisture, temperature, carbon availability, and pH [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], any disturbances or amendments might lead to the alteration of microbial activity and soil respiration dynamics. Basal respiration, typically measured via CO\u003csub\u003e2\u003c/sub\u003e release, primarily results from substrate availability in soil and provides fundamental information on microbial physiology and maintenance requirements. It thus serves as a measure of metabolic activity without quantifying the active microbial activity, as only the currently active microbes involved in respiration are recorded. In contrast, substrate-induced respiration (SIR) via the application of various substrates (e.g., glucose) can activate a broader spectrum of the soil microbiome, including previously dormant taxa [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This approach allows a more detailed assessment of microbial activity and functional diversity in soil with the quantity and range of utilized carbon sources reflecting microbial biomass abundance and community functional adaptability.\u003c/p\u003e \u003cp\u003eDespite the key role of microbial activity for diverse soil processes and soil properties, the specific interactions with and effects of PAA are subject to current research, especially with respect to soil moisture dynamics. This is mainly because most of the available studies are limited to the effect of SAPs on basic soil properties important for agriculture, like aggregate stability, porosity, OM content, and nutrient availability [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Consequently, we aimed to gain first insights into the concentration-, time-, and moisture dynamic-dependent effects of PAA on soil microbial activity and soil functional diversity. For this, a 10-week incubation experiment was performed with two soils, a loam and a sand, which were both treated with PAA at three different concentrations (25, 250, and 2500 mg PAA Kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e dry soil) and subjected to either constant moisture or drying-rewetting conditions. Throughout the incubation, both substrate-induced and basal soil respiration were recorded using MicroResp and headspace CO\u003csub\u003e2\u003c/sub\u003e measurements. In addition, the maximum water-holding capacity (WHC\u003csub\u003emax\u003c/sub\u003e) and the pH of the soils were monitored and changes in the soil structure were inveistigated using scanning electron microscopy (SEM).\u003c/p\u003e \u003cp\u003eWe expected that crosslinking between PAA molecules, driven by soil constituents such as polyvalent cations, along with PAA sorption to soil minerals and soil organic matter (SOM), will reduce the water absorption capacity of PAA in both soils. These effects should be further intensified by repeated drying and rewetting cycles. We hypothesized that increasing PAA concentrations will initially increase the WHC\u003csub\u003emax\u003c/sub\u003e of the PAA-treated soils; however, this effect should diminish over time, particularly when subjected to moisture dynamics. We propose that PAA-induced effects on soil pH and water binding will significantly modulate microbial activity: on the one hand, low PAA concentrations should enhance microbial respiration by improving water availability, whereas, on the other hand, high PAA concentrations should suppress respiration due to reduced soil pH and stronger water binding. Since PAA increases water retention during drying events and can thus alleviate drought stress, we expect that negative effects on soil microbial activity due to drying-rewetting dynamics will be mitigated. Negative effects of PAA and moisture dynamics, both individually and in combination, should be reflected in changed substrate usage patterns, in which simpler, more readily available carbon sources are preferred over complex compounds. However, since we assume that PAA will lose its functionality over time due to aging processes such as cementation accelerated by the drying-rewetting cycles [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], the respective effects on soil microbial respiration should decrease more rapidly under cyclic than static moisture conditions.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSoil samples and sample preparation\u003c/h2\u003e \u003cp\u003eTwo well-characterized reference soils (Lufa 2.1 and 2.4) from the Agricultural Analysis and Research Institute Speyer (LUFA, Speyer, Germany) were used in this study as typical agricultural soils. Their textures are classified as sand (Lufa 2.1) and loam (Lufa 2.4) with a pH of 4.6 and 7.5, and an organic carbon content (C\u003csub\u003eorg\u003c/sub\u003e) of 0.6% and 1.8%, respectively. An overview of selected soil physicochemical properties is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSelected physicochemical properties of the two investigated soils\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLufa 2.1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLufa 2.4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eloam\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSand (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSilt (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClay (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003csub\u003eorg\u003c/sub\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003csub\u003etot\u003c/sub\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH (0.01M CaCl\u003csub\u003e2\u003c/sub\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEC (meq 100 g\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWHC\u003csub\u003emax\u003c/sub\u003e (g 100 g\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBulk density (g cm\u003csup\u003e-3\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e \u003cp\u003eThe soils were oven-dried at 30\u0026deg;C for 4 days, subsequently spiked with high-weighted, linear polyacrylic acid (PAA) (M\u003csub\u003ev\u003c/sub\u003e = 4.000.000 g mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; ~ 0.1% cross-linkage) (Sigma-Aldrich, Germany) at three concentrations (25, 250 and 2500 mg PAA Kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), and manually homogenized for 10 minutes before moistening. Furthermore, control soils without PAA were prepared accordingly. The samples were subdivided into two groups based on the soil moisture conditions during the incubation time (constant moisture and drying-rewetting conditions). Half of the samples underwent ten drying-rewetting cycles, while the remaining samples were kept at static moisture conditions at 40% WHC\u003csub\u003emax\u003c/sub\u003e for the entire 10-week incubation period. All ten drying-rewetting cycles involved 1) a rapid (re)wetting event with ultrapure water, followed by 2) a three-day incubation period, and 3) a four-day drying phase at 30\u0026deg;C to complete dryness. At the cycles 0, 3, 5, and 10, corresponding to the respective incubation weeks, soil replicates for each treatment and control were taken and investigated for physicochemical properties and soil microbial activity. To improve readability, the term \u0026lsquo;measurement point\u0026rsquo; (MP) is used to include soil samples incubated under constant moisture conditions as well as cyclically dried and remoistened (e.g., measurement point 3 depicts incubation week 3 for the constant and the third drying-rewetting cycle for the cyclic soil samples, respectively).\u003c/p\u003e \u003cp\u003eAdditionally, pure PAA hydrogel was prepared to evaluate its swelling potential in the different soil solutions and demineralized water by allowing dry PAA powder to form a completely swollen hydrogel for 48 h with an excess of soil water (or demineralized water), which was extracted from the respective soils for 30 minutes at 2900 rpm using a MegaStar4.0 centrifuge (VWR, Germany) and 3D-printed polymer falcon tube centrifugation inserts [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. After 48 h, excess solution was separated from the swollen PAA hydrogel by centrifugation at 1000 \u0026times; \u003cem\u003eg\u003c/em\u003e for 20 min and the hydrogels were weighed to determine the amount of adsorbed solution per g dry PAA powder according to [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSoil physicochemical characterization\u003c/h3\u003e\n\u003cp\u003eWHC\u003csub\u003emax\u003c/sub\u003e (mL 100 g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e dry soil) of the soil samples was determined gravimetrically using the funnel method [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] based on the weight difference between the wet soil samples (S\u003csub\u003eW\u003c/sub\u003e / 100% WHC\u003csub\u003emax\u003c/sub\u003e) after 4 hours of saturation and 14 hours of gravitational draining, and the corresponding dry soil samples (S\u003csub\u003eD\u003c/sub\u003e / 0% WHC) after 4 days of drying at 105\u0026deg;C (Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{WHC}_{max}=\\frac{{S}_{W}-{S}_{D}}{{S}_{D}}*100$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eSoil pH was measured using a multimeter (Consort, Belgium) at the measurement points 0, 3, 5, and 10 following PAA addition for both soils to monitor changes in soil acidity under the different moisture regimes.\u003c/p\u003e\n\u003ch3\u003eMicrobial activity\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMicroResp\u003c/h2\u003e \u003cp\u003eSoil microbial respiration, including both basal and substrate-induced respiration, was measured using the MicroResp method [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. For each combination of soil type, PAA concentration, soil moisture condition, and measurement point, a 96-deepwell plate was prepared. The soil masses per well were 0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 g for sand and 0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 g for loam, respectively. For SIR measurements, eight different carbon substrates were used, which are representative due to their ecological relevance, their known occurrence in the soil environment (e.g. plant root exudates) and their ability to provide a sufficient range of structural complexity: Glucose (GLU), Galactose (GAL), L-alanine (ALA), N-acetylglucosamine (NAGA), α-cyclodextrin (ACYC), Trisodium citrate (CIT), ɣ-aminobutyric acid (GABA), and ultrapure water (WAT) as control. This resulted in 12 replicates per substrate and plate. For the analysis, the substrates were grouped into carbohydrates (GLU, GAL, ACYC), amines (ALA, NAGA, GABA), and carboxylic acids (CIT).\u003c/p\u003e \u003cp\u003eBefore substrate addition, the soils were preincubated at 40% WHC\u003csub\u003emax\u003c/sub\u003e for three days. Substrate application to each well resulted in the addition of 30 mg C ml\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil water and raised the soil moisture to 60% WHC\u003csub\u003emax\u003c/sub\u003e. CO₂ emissions were measured after 6 hours using a pH color reaction with cresol red as the indicator in the agar gel of the 96-well microplates that covered the deepwell plates during incubation. Light absorption at 572 nm, measured using a microplate spectrophotometer (Infinite M200, Tecan, Switzerland), was used to quantify the color change in the indicator gel due to the evolved CO\u003csub\u003e2\u003c/sub\u003e. Non-linear calibration data were used to convert the changes in light absorbance before and after the 6-hour incubation into respiration rates (\u0026micro;g CO\u003csub\u003e2\u003c/sub\u003e-C g⁻\u0026sup1; soil h⁻\u0026sup1;). SIR was calculated as the difference between the basal respiration rate (WAT) and the respiration rates from the various carbon sources. SIR values for each substrate, along WAT, were summed to determine the total substrate-induced respiration (SIR\u003csub\u003etot\u003c/sub\u003e). Additionally, the variation coefficient of the SIR values was calculated. The respiratory response to the substrate added reflects the proportion of active microbial biomass that is correspondingly able to use the respective carbon source.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHeadspace CO measurements\u003c/h3\u003e\n\u003cp\u003eHeadspace CO\u003csub\u003e2\u003c/sub\u003e measurements were conducted to obtain basal soil respiration by assessing the CO\u003csub\u003e2\u003c/sub\u003e concentration evolved in the headspace of the soil samples placed in incubation jars. Measurements were conducted according to [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] using a portable Los Gatos greenhouse gas analyzer (Los Gatos Research Inc, ABB Ltd, Switzerland) in a closed-loop setup. For this, the incubation jars were equipped with a Luer-lock connector, a three-way valve, an injection cap and two gaskets. This setup allowed headspace sampling without a permanent septum connection, reducing CO\u003csub\u003e2\u003c/sub\u003e loss. A preliminary experiment determined the CO\u003csub\u003e2\u003c/sub\u003e loss of the jars (n\u0026thinsp;=\u0026thinsp;5; 30\u0026thinsp;\u0026plusmn;\u0026thinsp;6 ppmv CO\u003csub\u003e2\u003c/sub\u003e h⁻\u0026sup1;), which was used as correction factor in the main experiment.\u003c/p\u003e \u003cp\u003eThe headspace measurements included three days of respiration, starting with each rewetting of a drying-rewetting cycle. Static samples were vented during the four-day drying period of the cyclic samples. Prior to the removal of the sampling volume (V\u003csub\u003es\u003c/sub\u003e = 500 \u0026micro;L), the headspace of the jars was homogenized by mixing the volume with a syringe attached to the three-way valve. The internal volume of the closed-loop setup (V\u003csub\u003el\u003c/sub\u003e), and thus the dilution factor, was determined prior to each measurement point using triplicate injections of standard gas with a known CO\u003csub\u003e2\u003c/sub\u003e concentration (20,000\u0026thinsp;\u0026plusmn;\u0026thinsp;400 ppmv). The CO\u003csub\u003e2\u003c/sub\u003e concentration of the samples (X\u003csub\u003es\u003c/sub\u003e; CO\u003csub\u003e2\u003c/sub\u003e in ppmv) was calculated according to Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e as the difference (ΔX) between the baseline gas concentration before the injection (X\u003csub\u003e0\u003c/sub\u003e) and the average equilibrium concentration (30 s) after injection (X\u003csub\u003ei\u003c/sub\u003e).\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:{X}_{s}=\\frac{{V}_{l}}{{V}_{s}}\\varDelta\\:X+{X}_{i}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAssuming standard conditions (P\u0026thinsp;=\u0026thinsp;1 atm, T\u0026thinsp;=\u0026thinsp;293.15 K) and knowing the partial volume of CO\u003csub\u003e2\u003c/sub\u003e in the samples (V\u003csub\u003eCO2\u003c/sub\u003e = ppmv x 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e * V\u003csub\u003eair\u003c/sub\u003e), the headspace volume (Sand: V\u003csub\u003eair\u003c/sub\u003e = 107.5 mL; loam: V\u003csub\u003eair\u003c/sub\u003e = 104.2 mL), and the universal gas constant (R\u0026thinsp;=\u0026thinsp;0.0821 L atm K\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) the ideal gas law was applied to convert ppmv into moles (n) per headspace. Using the molar mass of CO\u003csub\u003e2\u003c/sub\u003e (M\u0026thinsp;=\u0026thinsp;44.01 g mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), the soil dry weight (m) and incubation time (t), the results were expressed according to Eq.\u0026nbsp;\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e4\u003c/span\u003e in \u0026micro;g CO\u003csub\u003e2\u003c/sub\u003e-C g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and thus comparable to the results obtained from the MicroResp method.\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:x=\\frac{n*M}{t*m}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eScanning electron microscopy imaging\u003c/h2\u003e \u003cp\u003eTo qualitatively assess the effect of PAA on soil (micro)structural features scanning electron microscopy (SEM) images were taken with a FEI Quanta 250 ESEM (FEI Company Hillsboro, United States) using a secondary electron detector (SED) under high vacuum (\u0026lt;\u0026thinsp;10\u003csup\u003e\u0026minus;\u0026thinsp;4\u003c/sup\u003e Pa). Prior to the measurements, the samples were coated with a 30 nm thick layer of gold with a Quorum Q150R S sputter coater (Quorom Technologies Ltd, United Kingdom). The air-dried soil samples of measurement point 0 and 10 (both cyclic and static), either untreated or at 2500 mg PAA Kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil were exemplary selected for comparison.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData analysis was conducted using R version 4.3.0 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], employing a comprehensive statistical approach to examine soil parameters and microbial responses. A three-way analysis of variance (ANOVA) was used to evaluate the effects of PAA concentration, experimental time, and soil moisture regimes (sample type) on WHC\u003csub\u003emax\u003c/sub\u003e, soil pH, and microbial respiration results (stats package). Statistical assumptions were tested including normality of residuals using Q-Q plots and Shapiro-Wilk tests (stats package), homogeneity of variances through Levene's test (car package), and linearity via interaction plots. Post-hoc comparisons were performed using the Tukey HSD test (stats package). The F-value derived from the ANOVA represents the ratio of inter-group to intra-group variance, measuring the relative impact of each factor on the observed variables. It ranges from 0 to positive values, with higher F-values suggesting a stronger effect. The corresponding p-value assesses the significance of the respective effects, with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicating statistical significance. Omega squared (ω\u0026sup2;) was further calculated as an unbiased effect size estimate for each factor, ranging from 0 to 1, with higher values indicating a stronger influence of the independent variable on the dependent variable. For the headspace respiration data, a repeated measures ANOVA was applied (stats package), accounting for multiple measurements of the same sample over time.\u003c/p\u003e \u003cp\u003eA principal component analysis (PCA) was conducted to investigate relationships among soil physicochemical properties and microbial respiration variables (FactoMineR and factoextra packages). Continuous variables were standardized, and treatment conditions were incorporated as supplementary qualitative variables. The analysis was visualized through a biplot with 95% confidence interval ellipses, revealing complex interactions between experimental parameters.\u003c/p\u003e \u003cp\u003eDetailed statistical parameters, including F-values, p-values, and ω\u0026sup2;, are presented in Tables\u0026nbsp;2\u0026ndash;4 of the supplementary information (SI).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMaximum water holding capacity and soil pH\u003c/h2\u003e \u003cp\u003eWHC\u003csub\u003emax\u003c/sub\u003e measurements showed significant effects of PAA addition in both soils (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;2a in the SI). The swelling capacity of freely swollen PAA in extracted soil solutions was 56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 mL g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 mL g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for the sand and loam, respectively, and was thus significantly lower than in demineralized water (76.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 mL g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). For the sand, PAA concentration was the most significant factor (ω\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.79) affecting the WHC\u003csub\u003emax\u003c/sub\u003e variability (p\u0026thinsp;\u0026lt;\u0026thinsp;0.00001, df\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e \u003cp\u003eAlready at measurement point 0, increasing PAA concentrations significantly increased WHC\u003csub\u003emax\u003c/sub\u003e about 22%, from 25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 mL 100 g⁻\u0026sup1; soil at 0 mg PAA Kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil to 31\u0026thinsp;\u0026plusmn;\u0026thinsp;1 mL 100 g⁻\u0026sup1; soil at 2500 mg PAA Kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil. This effect persisted throughout the whole incubation time and for both cyclic and static soil moisture conditions. In addition, neither the incubation time, nor the number of drying-rewetting cycles, nor the soil moisture dynamics in general significantly affected the WHC\u003csub\u003emax\u003c/sub\u003e of the sand.\u003c/p\u003e \u003cp\u003eFor the loam, the PAA concentration (ω\u0026sup2; = 0.13; p\u0026thinsp;=\u0026thinsp;0.0004, df\u0026thinsp;=\u0026thinsp;3), the interaction between PAA concentration and sample type (ω\u0026sup2; = 0.12; p\u0026thinsp;=\u0026thinsp;0.0006, df\u0026thinsp;=\u0026thinsp;3), and sample type alone (ω\u0026sup2; = 0.03; p\u0026thinsp;=\u0026thinsp;0.0032, df\u0026thinsp;=\u0026thinsp;1) were the primary explanatory variables for WHC\u003csub\u003emax\u003c/sub\u003e variability. At measurement point 0, PAA significantly increased WHC\u003csub\u003emax\u003c/sub\u003e about 12.5%, from initially 47.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 mL 100 g⁻\u0026sup1; soil without PAA to 52.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 mL 100 g⁻\u0026sup1; soil at the highest PAA concentration. This increase remained significant under drying and rewetting, without further effects due to increasing cycles. Under static soil moisture conditions, the initial effect of PAA decreased over time, with no significant differences in WHC\u003csub\u003emax\u003c/sub\u003e compared to the control by measurement point 3. Although not statistically significant, WHC\u003csub\u003emax\u003c/sub\u003e showed a decreasing trend with increasing PAA concentrations in these weeks. Loam treated with the highest PAA concentration (2500 mg PAA Kg⁻\u0026sup1; soil) and subjected to drying-rewetting cycles revealed a significantly higher WHC\u003csub\u003emax\u003c/sub\u003e after 10 weeks compared to the respective soil incubated at constant soil moisture. When comparing the average increase in WHC\u003csub\u003emax\u003c/sub\u003e between the control and the highest PAA concentration for the cyclic samples, no significant differences (p\u0026thinsp;=\u0026thinsp;0.46) were observed between the sand (5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 mL 100 g⁻\u0026sup1; soil) and the loam (4.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 mL 100 g⁻\u0026sup1; soil).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSoil pH\u003c/h2\u003e \u003cp\u003ePAA significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, df\u0026thinsp;=\u0026thinsp;3) affected soil pH in both soils (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;2b in SI). In the sand, PAA significantly reduced the soil pH directly after application from 4.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 at 0 mg PAA Kg⁻\u0026sup1; soil to 3.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 at 2500 mg PAA Kg⁻\u0026sup1; soil. Although the pH successively re-increased over time, its reduction remained significant. The sand subjected to drying-rewetting cycles showed significantly higher pH values at measurement point 3 and after compared to the samples incubated at constant moisture conditions. The most significant factors for soil pH variability were the PAA concentration (ω\u0026sup2; = 0.37) and the incubation time (ω\u0026sup2; = 0.34).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e \u003cp\u003eIn the loam, PAA significantly reduced soil pH from initially 6.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 at 0 mg PAA Kg⁻\u0026sup1; soil to 6.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 at 2500 mg PAA Kg⁻\u0026sup1; soil. In contrast to the sand, the pH-reducing effect of PAA decreased over time, with pH values slightly (re-)increasing from measurement point 5 until the end of the experiment. At measurement point 10, the soil pH at constant moisture conditions increased from initially 6.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 at 0 mg PAA Kg⁻\u0026sup1; soil to 6.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 at 2500 mg PAA Kg⁻\u0026sup1; soil, whereas drying-rewetting cycles revealed pH changes from 6.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 at 0 mg PAA Kg⁻\u0026sup1; soil to 6.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 at 2500 mg PAA Kg⁻\u0026sup1; soil. Thus, the drying-re-wetting cycles led to significantly higher pH values from measurement point 3 onwards than under static soil moisture conditions. The most significant factors for soil pH variability were soil moisture condition (ω\u0026sup2; = 0.40, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;1) and the interaction of PAA concentration and time (ω\u0026sup2; = 0.30, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;9). All in all, the sand exhibited a higher pH reduction in response to PAA addition compared to the loam. Furthermore, the pH reduction in the sand was significant throughout the entire incubation time, whereas the loam showed an acidifying effect over time. At the end of the experiment (measurement point 10), both soils subjected to drying-rewetting cycles showed significantly higher pH values compared to the respective soils incubated at static moisture conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSoil microbial activity and functional diversity\u003c/h2\u003e \u003cp\u003eHeadspace CO\u003csub\u003e2\u003c/sub\u003e measurements were performed to assess the basal respiration activity of the two investigated soils as function of the incubation time, soil moisture regimes and PAA concentration (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). On the one hand, regardless of the incubation conditions (constant soil moisture vs. drying-rewetting cycles) and PAA concentration, both soils showed the same trend in terms of a high CO\u003csub\u003e2\u003c/sub\u003e release in the first week of incubation (measurement point 0), followed by a drastic drop and a constant respiration level from measurement point 3 onwards. Consequently, the incubation time was the primary factor (ω\u0026sup2; = 0.86, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3 for sand; ω\u0026sup2; = 0.94, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3 for loam) explaining the variability in basal respiration of both soils (Table\u0026nbsp;3 in SI). In comparison, the sand showed lower basal respiration rates overall than the loam.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOn the other hand, PAA reduced the basal respiration in the sand directly after addition (measurement point 0), from 1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 without PAA to 1.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 \u0026micro;g CO\u003csub\u003e2\u003c/sub\u003e-C g⁻\u0026sup1; soil h⁻\u0026sup1; at the highest PAA concentration (-30\u0026thinsp;\u0026plusmn;\u0026thinsp;2%). Interestingly, PAA increased the basal respiration in the loam, from 5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 without PAA to 9.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 \u0026micro;g CO\u003csub\u003e2\u003c/sub\u003e-C g⁻\u0026sup1; soil h⁻\u0026sup1; at the highest PAA concentration (+\u0026thinsp;62\u0026thinsp;\u0026plusmn;\u0026thinsp;6%). However, the effect of PAA disappeared within the first three incubation weeks and was no longer significantly different after measurement point 3. Soil moisture regimes showed no significant effects on the basal respiration of both soils investigated, neither alone nor in combination with PAA.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003c/p\u003e \u003cp\u003eIn both soils, total substrate-induced respiration (SIR\u003csub\u003etot\u003c/sub\u003e) significantly increased over time with the loam showing overall higher respiration rates than the sand (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb and Table\u0026nbsp;4 in SI). Mean SIR\u003csub\u003etot\u003c/sub\u003e in the sand increased for all PAA concentrations and soil moisture regimes, from 1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 at measurement point 0 to 2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 \u0026micro;g CO\u003csub\u003e2\u003c/sub\u003e-C g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at measurement point 10. Mean SIR\u003csub\u003etot\u003c/sub\u003e in the loam increased from 3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 at measurement point 0 to 5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 \u0026micro;g CO\u003csub\u003e2\u003c/sub\u003e-C g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at measurement point 10. In both soils, the observed fluctuations in SIR\u003csub\u003etot\u003c/sub\u003e were predominantly attributed to changes in substrate-specific microbial responses rather than alterations in baseline microbial activity. This is evidenced by the relatively constant basal respiration across treatments, contrasting with the more pronounced and variable changes in SIR patterns (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eFor the sand, basal and substrate-induced respiration rates increased for all substrate groups (carbohydrates, amines, and carboxylic acids) over time, with incubation time being the most significant factor explaining the variability (ω\u0026sup2; = 0.87, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). PAA significantly increased basal respiration (ω\u0026sup2; = 0.03, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3), while it reduced SIR for carbohydrates (ω\u0026sup2; = 0.11, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3), amines (ω\u0026sup2; = 0.13, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3) and carboxylic acids (ω\u0026sup2; = 0.14, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3). These effects remained consistent throughout the incubation time. Compared to the untreated control, SIR reductions at the highest PAA concentration were 90%, 54%, 100%, and 52% at measurement points 0, 3, 5, and 10, respectively. Thus, the highest PAA concentration led to complete SIR suppression, particularly at measurement points 0 and 5. At the end of the incubation time, soil samples subjected to drying-rewetting cycles exhibited higher basal respiration rates (+\u0026thinsp;7.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09%) than under static moisture conditions. Conversely, for all SIR groups, static soil moisture induced higher respiration rates than drying-rewetting cycles at PAA concentration up to 250 mg Kg\u003csup\u003e-1\u003c/sup\u003e soil (+\u0026thinsp;85\u0026thinsp;\u0026plusmn;\u0026thinsp;12%). At the highest PAA concentration, however, the two soil moisture regimes showed no significant differences anymore.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003c/p\u003e \u003cp\u003eThe SIR variation coefficients underscored these findings as they increased over time (ω\u0026sup2; = 0.12, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3) but decreased with higher PAA concentrations (ω\u0026sup2; = 0.14, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3), nearly dropping to zero during the initial weeks of incubation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eComparable to the sand, both basal and substrate-induced respiration rates of the loam increased over time and for all substrate groups. However, in contrast to the sand, the basal respiration increased only at low PAA concentrations (ω\u0026sup2; = 0.08, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3), while the highest PAA concentration significantly reduced basal respiration. Comparing the control and the highest PAA concentration, the overall basal respiration decreased by 7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3% at the beginning of the incubation for the SIR of carbohydrates, amines, and carboxylic acids. Interestingly, the effect of PAA addition on SIR was less consistent in the loam compared to the sand, with the two moisture regimes showing opposite responses: under drying-rewetting cycles, SIR respiration increased with increasing PAA concentration, whereas SIR respiration in static soil moisture decreased. Comparing the control and the highest PAA concentration, the overall SIR of the loam under static soil moisture conditions was reduced by 75\u0026thinsp;\u0026plusmn;\u0026thinsp;1% after 10 weeks. Here, the highest respiration suppression of 83\u0026thinsp;\u0026plusmn;\u0026thinsp;15% was observed for carbohydrates (4.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 to 0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 \u0026micro;g CO\u003csub\u003e2\u003c/sub\u003e-C g\u003csup\u003e-1\u003c/sup\u003e soil h\u003csup\u003e-1\u003c/sup\u003e). Although less pronounced, the same pattern was observed for amines and carboxylic acids.\u003c/p\u003e \u003cp\u003eFrom measurement point 5 on, the loam incubated at static moisture conditions consistently showed higher basal respiration rates compared to the respective samples subjected to drying-rewetting cycles. Also, the SIR rates were consistently higher from measurement point 3 onward at static soil moisture conditions than at drying-rewetting cycles. After 10 weeks, the loam incubated under static moisture conditions exhibited a 12.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1% increase in basal respiration and a 487\u0026thinsp;\u0026plusmn;\u0026thinsp;62% increase in SIR when either untreated or treated with low PAA concentrations (up to 250 mg PAA Kg\u003csup\u003e-1\u003c/sup\u003e soil). As with the sand, the differences in loam decreased with increasing PAA concentration and for soil moisture regimes, with no significant differences anymore at the highest PAA concentration. The SIR variation coefficient for the loam further supports these findings, showing a significant increase over time (ω\u0026sup2; = 0.15, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3). While PAA concentration (ω\u0026sup2; = 0.02, p\u0026thinsp;=\u0026thinsp;0.0005, df\u0026thinsp;=\u0026thinsp;3) still slightly contributed to the variation, its effect was less pronounced than in the sand. In contrast, the sample type (ω\u0026sup2; = 0.06, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;1) had a stronger influence on the variation in the loam, particularly towards the end of incubation, as demonstrated by its significant interaction with the incubation time (ω\u0026sup2; = 0.07, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, df\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRelationships between the parameters investigated\u003c/h2\u003e \u003cp\u003eFor the sand, PCA indicated that the first two principal components explained 82.5% of the total variance, with PC1 accounting for 58.1% and PC2 for 24.4% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). PC1 was primarily influenced by SIR variables, including carboxylic acids, amines, and carbohydrates. PC2 was dominated by WHC\u003csub\u003emax\u003c/sub\u003e and soil pH. A negative correlation was observed between soil pH and WHC\u003csub\u003emax\u003c/sub\u003e. SIR variables were positively correlated with each other and showed no correlation with WHC\u003csub\u003emax\u003c/sub\u003e or soil pH.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003c/p\u003e \u003cp\u003eThe PCA biplot (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) revealed no distinct clustering based on the two soil moisture regimes: drying-rewetting cycles tended towards higher soil pH values, while static soil moisture conditions displayed a broader distribution along PC1 with higher respiration rates. Clustering based on PAA concentration (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) was more pronounced along PC2, where higher PAA concentrations were associated with increased WHC\u003csub\u003emax\u003c/sub\u003e and lower soil pH values. Basal respiration rates did not show any clear clustering patterns between incubation conditions or substrate groups. However, for the SIR variables, the highest PAA concentration corresponded to the lowest respiration rates compared to the lower PAA concentrations and the control. The most distinct separation of samples was based on the measurement points, with measurement point 10 clearly separated from earlier points, indicating higher respiration rates along PC1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor the loam, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb-\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e indicated that the first two principal components explained 76.4% of the total variance, with PC1 accounting for 58.0% and PC2 for 18.3%. Similar to the sand, PC1 was dominated by SIR variables, while PC2 by WHC\u003csub\u003emax\u003c/sub\u003e and soil pH. Again, soil pH was negatively correlated with WHC\u003csub\u003emax\u003c/sub\u003e, and the SIR variables were positively correlated with each other, showing no distinct relationship with WHC\u003csub\u003emax\u003c/sub\u003e or soil pH. The PCA biplot (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb-\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) revealed distinct clustering based on the soil moisture regimes: soil samples subjected to drying-rewetting cycles tended to higher soil pH values, while static soil moisture conditions exhibited a broader distribution along PC1, with notably higher respiration rates. Clustering based on PAA concentration was apparent along PC2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), with higher PAA concentrations associated with increased WHC\u003csub\u003emax\u003c/sub\u003e and reduced soil pH. At the highest PAA concentration, both basal respiration and SIR exhibited lower respiration rates and a narrower distribution along PC1 compared to the control and lower PAA concentrations. Clustering by measurement points (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) was distinct, with measurement point 10 clearly separated from earlier points, reflecting higher respiration rates along PC1. Over time, the cluster distribution shifted from a wider spread along PC2 to a broader distribution along PC1. This indicates that the influence of PAA concentration on soil pH and WHC\u003csub\u003emax\u003c/sub\u003e of the loam diminished over time.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eScanning electron microscopy\u003c/h2\u003e \u003cp\u003eAlthough the SEM images did not show noticeable differences based on measurement point or soil moisture regimes for both soils, they clearly showed membranous PAA structures between the soil particles, forming particle coatings as well as interparticulate bridges and connections of varying sizes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). At higher magnification, the bridging and coating effects of PAA became even more evident, revealing that the PAA membrane network not only bonded soil particles but also organic material.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the impact of PAA on maximum water holding capacity (WHC\u003csub\u003emax\u003c/sub\u003e) and soil pH, and how these changes affected soil microbial activity in a sand and loam under different moisture conditions. PAA increased WHC\u003csub\u003emax\u003c/sub\u003e in both soils, with loam revealing higher WHC\u003csub\u003emax\u003c/sub\u003e under drying-rewetting cycles. PAA decreased soil pH in both soils, with a stronger reduction in the sand, where it remained significant throughout the incubation time. Basal respiration decreased in the sand with increasing PAA concentration, while it increased in the loam, especially at low PAA concentrations. Substrate-induced respiration (SIR) was suppressed in both soils, particularly in sand at high PAA concentrations, and even stronger under static moisture conditions. All in all, the effect of PAA on SIR varied with moisture regime, decreasing under static moisture conditions and increasing under drying-rewetting cycles at relatively lower PAA concentrations.\u003c/p\u003e \u003cp\u003eAs hypothesized, PAA significantly increased WHC\u003csub\u003emax\u003c/sub\u003e in both investigated soils. This is in line with various other studies investigating the effect of SAPs on soil WHC\u003csub\u003emax\u003c/sub\u003e, although the effect size partly differed considerably [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. For example, [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] investigated four crosslinked acrylamide and acrylic acid polymers in a sandy soil with similar grain size distribution, CEC, and C\u003csub\u003eorg\u003c/sub\u003e, but different application types (powder vs. granules of up to 2 mm). The four polymers applied at a concentration of 2500 mg Kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil increased the water content of the sandy soil by roughly 65%, corresponding to a PAA absorption capacity of roughly 90 mL water g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e polymer. In this study, the PAA powder only absorbed 22 mL water g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in the sand. This finding highlights the influence of the application type on the efficiency of PAA to improve water retention in soil: the relatively lower surface area of PAA granules compared to powder allows for the creation of a more stable, local hydrogel network, which can counteract the confining pressure and suction tension of the soil matrix effectively [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In contrast, PAA powder provides a relatively high surface area, which promotes strong and fast interactions with soil particles, e.g., in terms of their adsorption, typically reducing their swelling potential [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Furthermore, dispersion effects of PAA polymer when homogeneously mixed into the soil might prevent the formation of a strong, spatially interconnected network that can withstand the confining pressure of the soil matrix and efficiently absorb water from its surroundings [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInterestingly, the positive effect of PAA on the WHC\u003csub\u003emax\u003c/sub\u003e of both investigated soils was not completely reduced over time or with increased drying-rewetting cycles. Even after 10 drying-rewetting cycles, the PAA-induced WHC\u003csub\u003emax\u003c/sub\u003e remained relatively stable for the sand and showed a linear increase with increasing PAA concentration, suggesting a concentration-independent behavior. This contrasts [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] who reported a reduced water absorbance of SAPs in ultrapure water, tap water, and soil extracts with increasing drying-rewetting events. They also noted that the extent of the functional loss was related to the severity of the drying events. Despite fully drying the soils in this study during the respective drying-rewetting cycles, representing such typical severe drying events, no decline in water retention was observed after rewetting.\u003c/p\u003e \u003cp\u003eWhile PAA retained its functionality in the sand under both moisture regimes, the situation was different in the loam: here PAA lost its functionality completely over time and, in addition to the loss of additional PAA-induced water uptake, the WHC\u003csub\u003emax\u003c/sub\u003e was even lower compared to the control. In this context, freely swollen PAA in the respective soil solutions also showed a significantly lower swelling capacity compared to demineralized water, especially when swollen in the loam soil solution. These effects are likely due to cation-mediated crosslinking between PAA polymer chains, solution salinity and pH effects that restrict hydrogel network expansion and water absorption into the three-dimensional PAA hydrogel network [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Especially the ionic strength in the soil solutions reduces the osmotic pressure difference between PAA and the solvent, whereas low solution pH promotes cation release and consequently PAA crosslinkage and PAA-mineral interactions in soil [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The results showed that the initial PAA treatment lowered the soil pH in both soils, most likely due to the dissociation of carboxylic acid groups releasing hydrogen ions [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. This effect persisted in the sand but disappeared in the loam after one week. Here, favorable pH buffer conditions in terms of higher CEC and C\u003csub\u003eorg\u003c/sub\u003e in the loam (three times that of sand) might have stabilized the soil pH, e.g., through functional groups in OM or exchange at clay mineral surfaces [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUnder static conditions, PAA completely lost its positive effects on the WHC\u003csub\u003emax\u003c/sub\u003e of the loam after 10 weeks and even reduced it compared to the untreated control, likely because the nearly neutral solution in loam under drying-rewetting conditions and the acidic conditions in the sand resulted in comparable ionic strength and crosslinking environments. On the one hand, static moisture conditions likely promoted cation release into the soil solution, enabling ionic crosslinking of PAA polymer chains and polymer-clay interactions [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. On the other hand, the physical limitation of soil particles and water competition with other reactive soil components such as SOM and clay particles also limited PAA swelling [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Existing studies have demonstrated that water redistribution in the soil matrix occurs as a function of capillary forces and the spatio-temporal (re)wetting of mineral surfaces. This process is followed by the gradual dehydration of the interparticulate SAP hydrogel over time, reaching an equilibrium state between the spatially condensed interparticle gel network and the surrounding soil matrix [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurther, the relatively lower pH environment in the loam may have further promoted the availability of cations by successively releasing them from cation exchangers under static moisture conditions, which further enhanced the crosslinking effect between the PAA polymer chains themselves and the cementation in the interparticle space via polymer-clay interactions and successive dehydration [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. While the soils subjected to drying-rewetting cycles experienced only three days of moist conditions before the next drying event, the static samples had a continuous period for these processes to progress without interruption. Thus, the dynamic nature of the drying-rewetting cycles likely interrupted striking processes and thereby prevented irreversible PAA dehydration in the interparticle space. However, [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] immersed different hydrogels in solutions containing varying concentrations of divalent ions such as Cu(II) and Zn(II) and measured their swelling degrees after two hours. Besides demonstrating a significant reduction in hydrogel swelling with increasing ion concentrations, the authors showed that crosslinking processes occur relatively quickly. This indicated that the disruption of PAA hydrogel crosslinking due to drying-rewetting cycles were not the driving factor in the investigated loam. In addition, increased aeration while drying lead to a reduction in CO\u003csub\u003e2\u003c/sub\u003e concentration, raising the soil pH and mitigating the pH-reducing effects of PAA via reducing carbonic acid formation and lowering hydrogen ion concentrations [\u003cspan additionalcitationids=\"CR50 CR51\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. The higher pH, combined with changes in ionic strength due to the drying-rewetting process, likely helped preserve the swelling ability of PAA in the soil interparticle space. This emphasizes the need for future studies to investigate the role of drying-rewetting cycles of different durations, including partial drying events to deepen the understanding of the underlying mechanisms and their impact on the performance of hydrogels under real conditions. In addition, monitoring the ionic strength and concentration of potential PAA crosslinking ions during drying-rewetting cycles would provide further important insights into the relevance of changing chemical soil solution properties.\u003c/p\u003e \u003cp\u003eThe measured basal respiration for both soils were within the range reported in other studies, with a tendency for higher respiration rates observed under static moisture conditions compared to drying-rewetting conditions [\u003cspan additionalcitationids=\"CR54 CR55\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Repeated drying-rewetting cycles typically impose osmotic and oxidative stress on microbial communities, leading to cell lysis, which reduces microbial biomass, shifts in microbial energy use, as microbes divert resources toward stress recovery mechanisms, such as repairing cell membranes or producing osmolytes, rather than towards respiration [\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. This stress also tends to reduce microbial diversity, with stress-tolerant microbes becoming more dominant. Conversely, in static moisture treatments, microbial communities experience fewer disruptions, allowing them to maintain a more stable environment [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. This stability enables higher metabolic activity and basal respiration rates, as microbes can focus more energy on growth and maintenance rather than stress recovery. Thus, the differences in respiration rates between static and cyclic moisture conditions reflect the broader impacts of moisture fluctuations on microbial community dynamics and function.\u003c/p\u003e \u003cp\u003eConcerning the differences in basal respiration as function of the two soil types, the loam consistently showed higher microbial respiration rates than the sand, which aligns with existing literature linking basic soil physicochemical properties such as soil pH, soil carbon content and soil water availability to soil respiration [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. One key factor explaining the differences in microbial respiration between the soils is the pH, a well-established determinant of microbial activity and community composition. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] identified a critical threshold at pH 5.5, below which microbial carbon use efficiency and respiration tend to decline. While the loam consistently maintained pH values above this threshold across all PAA concentrations, the sand exhibited lower pH values, likely contributing to its generally reduced respiration rates. This could also explain the relatively lower SIR response to added carbon sources in the sand compared to the loam, respectively. In line with [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], the results suggest that the microbial community in the loam exhibited a higher capacity to decompose the added substrates, whereas the microbial community in the sand was less responsive to changes in resource availability. [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e] found similar results, observing a stronger increase in respiration with rising carbon content in a clay loam compared to a loamy sand.\u003c/p\u003e \u003cp\u003eAlthough PAA significantly affected soil microbial respiration in a concentration-dependent manner, the results suggest that respiration patterns cannot be solely attributed to PAA. Instead, they likely reflect complex interactions with other factors, including soil pH, WHC\u003csub\u003emax\u003c/sub\u003e, incubation time, and moisture dynamics. Contrary to our expectations and current scientific knowledge, PAA showed no clear drought-mitigating effect in the two investigated soils. Further, it did not lose its effects on soil microbial respiration over time or due to moisture dynamics. Depending on the concentration, PAA reduced soil microbial respiration in both soils and shifted substrate usage patterns, indicating a lower capacity to utilize added carbon sources for the respective microbial communities. Since PAA is well-known to be mostly non-biodegradable [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], the effects on soil microbial activity are mainly not attributed to the utilization of PAA-derived carbon. In nature and as shown by SIR, the reduced utilization of easily degradable carbohydrates at high PAA concentrations suggests enzyme inhibition, such as of amylases, likely due to a decreased abundance of carbohydrate-utilizing microbes. For more complex substrates like amines and carboxylic acids, which require specialized metabolic pathways (e.g., deamination for amines and beta-oxidation for carboxylic acids), the reduced utilization at high PAA concentrations suggests similar inhibitory effects. These may include the induction of oxidative stress and pH shifts, which suppress microbial metabolism, as it has been shown for other polymers such as polyethylene and polylactic acid [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Respective changes could lead to a shift in microbial community structure, favoring microbes that metabolize simpler substrates over those capable of degrading more complex compounds. Further, changes in soil pH might have directly influenced soil microbial activity, as certain microbial groups are more adapted to pH ranges or resilient to pH changes. Thus, pH shifts might favor or inhibit acidophilic or alkaliphilic microorganisms, potentially disrupting the overall balance of the soil microbial community and impairing their ability to process organic matter [\u003cspan additionalcitationids=\"CR68\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSoil moisture conditions also contributed to the PAA-induced effects on soil microbial respiration, as both excessive and insufficient moisture levels can reduce respiration rates: High water content can limit oxygen availability by filling pore spaces and consequently restricting aerobic microbial processes [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Here, SAPs, like PAA, may promote this effect by further occupying the available soil pore spaces during their swelling, thereby reducing soil permeability and pore interconnectivity [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], a phenomenon also observed for natural compounds, such as bacterial polysaccharides and EPS [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Conversely, limited water availability can inhibit soil microbial respiration by reducing substrate and nutrient accessibility and causing cytoplasmic dehydration in soil organisms [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. While SAPs have been shown to increase overall soil water content [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], the relative proportion of water available to the soil microbial community may decrease, exacerbating the respiration-limiting effects associated with low water availability [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the sand, both moisture regimes had a consistent negative effect on PAA-induced soil respiration, whereas this negative effect was only observed under static moisture conditions in the loam. This can be attributed to their differences in soil texture, water retention capacity, and microbial community responses. In general, soil moisture fluctuations induced by drying-rewetting events can create osmotic and oxygen stress that can damage microbial cells and reduce microbial biomass [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Additional PAA exposure under these fluctuating conditions might exacerbate those stresses and consequently further reduce soil respiration. On the one hand, sands, with their low water-holding capacity, face limited moisture availability under both static and drying-rewetting conditions [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. Together with the PAA-induced water competition and oxidative stress, it further restricts soil microbial activity and respiration. On the other hand, loams can retain more water, which might allow microbes to recover more effectively during drying-rewetting cycles, partly mitigating the negative impact of PAA. Furthermore, soil drying, along with interparticulate PAA dehydration and soil pore aeration, could improve oxygen availability and reduce oxidative stress caused by PAA. Both [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] demonstrated that the addition of SAP reduces water evaporation rates during drying events, leading to higher soil water content over an extended period. This effect could mitigate drought stress by maintaining suitable conditions for soil microbes, thereby supporting higher microbial respiration for a longer duration. In the sand, enhanced aeration from drying-rewetting cycles may not have been sufficient to counteract the negative impacts of PAA, as sand typically has better aeration properties. Therefore, differences in aeration between constant and drying-rewetting conditions might be smaller in the sand compared to the loam. At this point, it is important to note that the complex interactions and mechanisms proposed have not been explored in detail yet. Thus, the initial insights from this study suggest potential relationships between PAA exposure, soil respiration, and microbial activity, highlighting the need for further systematic research. Besides soil pH, WHC\u003csub\u003emax\u003c/sub\u003e, and soil moisture, other soil-specific physicochemical properties and processes, as influenced by PAA, should also be considered, e.g., soil aggregation, pore structure recreation, and the potential formation of solid SAP residues: On the one hand, PAA is well-known to alter soil aggregation and to spatio-temporal redistribute soil micro- and macroaggregates, playing a crucial role in defining microhabitats, moisture availability, and soil aeration [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Changes in soil porosity and soil pore structures can alter water and air movement, potentially leading to respective limitations that further suppress microbial activity. For example, larger aggregate sizes, as promoted by PAA, are generally associated with lower respiration rates and higher fungi-to-bacteria ratios compared to smaller ones [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, interparticulate PAA hydrogel might form solid residues over time or upon drying-rewetting, which could further reduce soil pore interconnectivity due to their cemented solid structures over larger interparticle areas. However, the extent, duration and relevance of this process is still poorly understood and is currently the focus of research [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough our study provided valuable first insights into the effect of PAA on soil microbial activity and substrate utilization, there are several areas that should be further exploration and investigation to deepen our understanding: one key but typical limitation is the limited diversity of substrates used in studies, which may not fully reflect the range of OM utilized by soil microbes. Thus, including a broader variety of substrates could provide a more comprehensive view of microbial processes under PAA exposure. Additionally, while shifts in microbial community composition are suggested, detailed profiling of microbial groups and their functional pathways is still lacking, which could be addressed using advanced molecular techniques, such as metagenomics [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Although two soils have been investigated in this study, the variability in soil types and long-term effects of PAA exposure also remain underexplored, highlighting the need to conduct systematic studies with different soil types and implementing long-term exposure assessments. Furthermore, environmental factors potentially interacting with PAA-induced changes in soil (e.g., pH shifts and oxidative stress) need more attention in multi-stressor studies. Finally, the exact mechanisms behind the ecotoxicological impact of PAA on soil microbiology, such as enzyme inhibition or oxidative stress, require further targeted biochemical investigations [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that PAA significantly alters WHC\u003csub\u003emax\u003c/sub\u003e and soil pH, with subsequent effects on soil microbial activity as function of concentration, soil type and moisture dynamics. PAA increased WHC\u003csub\u003emax\u003c/sub\u003e in both sand and loam by absorbing available water into its three-dimensional interparticulate hydrogel network, but its effect intensity and duration varied, persisting in sand while declining in loam due to ionic crosslinking and pH-buffering effects. PAA further reduced soil pH, particularly in the sand, which remained acidic throughout the incubation period, while the loam exhibited a transient pH decrease.\u003c/p\u003e \u003cp\u003eConcerning the effect of PAA on soil microbial activity, low PAA concentrations seem to temporarily stimulate soil respiration, e.g. by facilitating water and nutrient uptake and causing temporary positive stress due to short-term pH changes in soil. However, at higher concentrations, PAA tends to exert inhibitory effects, probably through oxidative stress, enzyme inhibition, or microbial community shifts. The observed suppression of substrate-induced respiration (SIR), especially for more complex substrates such as amines and carboxylic acids, indicates that PAA impairs microbial functional diversity and thus potentially also the entire biochemical cycle in soil. The strong interactions between PAA-induced effects and soil moisture conditions highlight its role in modulating microbial activity: while static moisture conditions increased PAA-induced suppression, drying-rewetting cycles mitigated some negative effects but also introduced additional stress, probably through osmotic fluctuations, oxidative stress, and enzyme disruption. Furthermore, PAA seems to indirectly affect soil microbial activity by modulating soil physical properties, such as soil porosity, or forming solid SAP residues and should be further investigated. All in all, this study highlights the importance of considering both chemical and physical stressors when assessing the application of PAA as soil amendment and its effect on soil microbiology. Since the soil type modulated the magnitude of PAA-induced effects and given the widespread use of SAPs in agriculture and land management, a more comprehensive understanding of their long-term effects on soil microbial communities, nutrient cycling, and ecosystem stability is critical. Thus, future should investigate soil microbial adaptation mechanisms, the persistence of PAA in soil, and potential mitigation strategies to balance the benefits of SAPs with their environmental impact on soil health and ecosystem functioning.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eCompeting Interests:\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFinancial support\u003c/strong\u003e \u003cp\u003eThis research was financially supported by the Deutsche Forschungsgemeinschaft (Grant No. BU 3763/1\u0026ndash;1).\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: C.B., Z.S., S.R., and J.N.; Methodology and experimental setup: C.B., Z.S., S.R., and J.N.; Material preparation and data collection: S.R.; Data evaluation and interpretation: S.R., C.B., and Z.S.; Writing - original draft preparation: S.R. and C.B.; Writing - review and editing: S.R., Z.S., J.N., and C.B.; Funding acquisition: C.B.; Project management: C.B.; Supervision: C.B. and Z.S.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe kindly thank Gabriele E. 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Y. \u0026amp; Ferrari, B. J. D. \u003cem\u003eEcotoxicological effects of polyacrylate, acrylic acid, polyacrylamide and acrylamide on soil and water organisms\u003c/em\u003e (Swiss Centre for Applied Ecotoxicology, 2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Polyacrylic acid, Soil amendment, Soil microbial activity, Substrate-induced respiration, Soil water holding capacity, Drying-rewetting cycles","lastPublishedDoi":"10.21203/rs.3.rs-6225306/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6225306/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePolyacrylic acid (PAA), a synthetic superabsorbent polymer (SAP), enhances the maximum water holding capacity (WHC\u003csub\u003emax\u003c/sub\u003e), stability, and aeration of soil but may directly or indirectly impact the soil microbiome by altering soil properties. However, respective studies on its effects on microbial activity in terms of respiration and functional diversity remain scarce.\u003c/p\u003e \u003cp\u003eIn this study, we examined the impact of PAA on soil microbial activity in a sand and loam treated with PAA at three concentrations (25, 250, 2500 mg Kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and either incubated under constant moisture or ten drying-rewetting cycles. During incubation, soil WHC\u003csub\u003emax\u003c/sub\u003e, pH, and microbial activity were measured via headspace CO\u003csub\u003e2\u003c/sub\u003e and MicroResp assay.\u003c/p\u003e \u003cp\u003ePAA increased WHC\u003csub\u003emax\u003c/sub\u003e in both soils and remained stable, except in loam under static moisture. Initially, PAA lowered pH in both soils, which persisted only in sand and disappeared in loam after one week. Further, drying-rewetting cycles raised pH in both soils compared to static conditions. PAA suppressed substrate-induced respiration (SIR) for carbohydrates, amines, and carboxylic acids, particularly in the sand, where high concentrations led to up to 100% suppression. Responses in the loam varied: drying-rewetting cycles increased, while static conditions reduced microbial respiration at higher PAA concentrations, respectively.\u003c/p\u003e \u003cp\u003eOverall, PAA reduced microbial activity in sand, whereas moisture regimes and soil texture were dominant factors in loam. This highlights the dual impact of SAPs: improving water retention in a certain period, while potentially reducing soil microbial activity and nutrient cycling, depending on soil type, application rates, and environmental conditions. In the long term.\u003c/p\u003e","manuscriptTitle":"Impact of polyacrylic acid as soil amendment on soil microbial activity under different moisture regimes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-26 18:27:03","doi":"10.21203/rs.3.rs-6225306/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-21T10:39:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-19T10:06:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"124648995184652872152435816569401825397","date":"2025-04-09T04:34:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-03T15:37:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"221771572614059195503088784094652474975","date":"2025-03-25T12:59:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-25T01:08:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-25T01:01:42+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-21T14:51:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-20T11:06:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-14T10:25:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1d034a34-3993-4f1b-b4e3-657f970d8410","owner":[],"postedDate":"March 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46192496,"name":"Biological sciences/Microbiology"},{"id":46192497,"name":"Earth and environmental sciences/Biogeochemistry"},{"id":46192498,"name":"Earth and environmental sciences/Environmental sciences"},{"id":46192499,"name":"Earth and environmental sciences/Natural hazards"},{"id":46192500,"name":"Earth and environmental sciences/Solid earth sciences"},{"id":46192501,"name":"Physical sciences/Materials science"}],"tags":[],"updatedAt":"2025-06-09T16:06:23+00:00","versionOfRecord":{"articleIdentity":"rs-6225306","link":"https://doi.org/10.1038/s41598-025-04457-8","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-06-03 15:57:22","publishedOnDateReadable":"June 3rd, 2025"},"versionCreatedAt":"2025-03-26 18:27:03","video":"","vorDoi":"10.1038/s41598-025-04457-8","vorDoiUrl":"https://doi.org/10.1038/s41598-025-04457-8","workflowStages":[]},"version":"v1","identity":"rs-6225306","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6225306","identity":"rs-6225306","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}