Soil enzyme dynamics in arid and Mediterranean soils exposed to environmentally relevant PFAS concentrations

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Sanchez-Hernandez, Natividad I. Navarro Pacheco, Ximena Andrade Cares, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9247907/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract This study investigated the short- and long-term effects of perfluorooctanoic acid (PFOA) and 6:2 fluorotelomer sulfonic acid (6:2 FTSA) on the biochemical functioning of agricultural soils with contrasting organic matter content, specifically Mediterranean and arid soils. Soil samples were spiked with environmentally relevant concentrations of both PFAS (10, 50, and 250 ng g⁻¹ dry mass) and incubated for 210 days to monitor changes in microbial and enzymatic activities. The results revealed that both PFAS significantly impaired soil biochemical functioning in the arid soil, with Treated-Soil Quality Index (T-SQI) values declining to less than 70% of control levels. Specifically, 6:2 FTSA caused significant inhibition of carbon- and phosphorus-acquiring enzymes such as β-glucosidase and alkaline phosphomonoesterase, with inhibition levels reaching up to 81.7%. In contrast, the Mediterranean soil exhibited minimal enzymatic response, which was attributed to its higher organic matter content that likely decreased PFAS bioavailability. Eco-enzymatic stoichiometric modeling further indicated that PFAS exposure increased microbial carbon limitation and altered nutrient acquisition strategies in arid soils over the long term. While PFOA concentrations remained relatively stable throughout the study, 6:2 FTSA underwent microbially mediated transformation to perfluoroheptanoic acid (PFHpA), with more pronounced dissipation occurring in the Mediterranean soil. Overall, these findings highlight the greater vulnerability of low-organic matter arid soils to both legacy and emerging PFAS, emphasize the risk of impaired nutrient cycling associated with PFAS-contaminated organic amendments, and underscore the importance of careful management of biosolids and municipal composts in dryland agricultural systems. Earth and environmental sciences/Biogeochemistry Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Biological sciences/Microbiology PFOA 6:2 FTSA soil enzymes eco-enzymatic stoichiometry enzymatic index arid soils Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Sustainable agriculture promotes the use of organic amendments such as composts and biosolids as a strategy to enhance soil fertility and crop productivity [ 1 ]. This practice is particularly recommended in regions characterized by low soil organic matter content, including Mediterranean areas and arid environments [ 2 ]. However, the application of these organic amendments may pose long-term environmental and human health risks due to contaminants that may be present in reclaimed wastewater, municipal composts, and biosolids [ 3 ]. Among these contaminants, per- and polyfluoroalkyl substances (PFAS) are frequently detected in such materials [ 4 – 6 ]. PFAS are used extensively in industrial, commercial, and consumer products, including food packaging, waterproof textiles, cosmetics, paints, non-stick cookware, papermaking, oil production, mining, metal plating, electronics, and fire-fighting foams [ 7 ]. Their high chemical stability and resistance to environmental degradation have resulted in widespread contamination of ecosystems, including remote regions [ 8 ]. Among the numerous PFAS compounds, perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) are the most frequently detected PFAS in many environmental compartments. Despite their inclusion in the Stockholm Convention on Persistent Organic Pollutants, which has led to global restrictions on their production and use, both chemicals continue to be detected in sewage sludges. Reported concentrations range from 1 to 5,383 ng g ‒1 for PFOA, and from 0.5 to 4,780 ng g ‒1 for PFOS [ 9 ]. Consequently, agricultural soils amended with biosolids often contain substantial PFAS loads, with concentrations reaching to 2,531 ng g ‒1 for PFOA and 5,500 ng g ‒1 for PFOS [ 8 ]. In response to regulatory actions driven by their high environmental persistence, bioaccumulation potential, and chronic toxicity, industries have introduced emerging PFAS alternatives characterized by structural modifications. These include shorter fluorinated carbon chains, the incorporation of oxygen bridges, or the partial substitution of fluorine atoms with hydrogen or other halogens, with the aim of reducing environmental persistence and toxicity [ 10 ]. One example of these emerging PFAS is 6:2 fluorotelomer sulfonic acid (6:2 FTSA), a widely used substitute for PFOS that is now also detected in wastewater treatment plants and biosolids [ 11 , 12 ]. Moreover, recent studies reveal that many emerging PFAS exhibit toxicity comparable to those of legacy PFAS, raising concerns about their long-term environmental and health impacts [ 13 ]. Although agricultural soils represent major sinks for PFAS, knowledge about their ecological impacts on soil functioning remains limited. Nevertheless, several studies have shown that PFAS can alter soil physicochemical and biological properties. For example, PFOS and 6:2 FTSA have been shown to affect bacterial richness, diversity, and functional capabilities in PFAS-spiked soils, with long-chain PFAS exerting stronger effects than short-chain analogues [ 14 ]. Similarly, PFOA has been reported to influence soil microbial and enzymatic activity depending on the fertilization regime, alkaline phosphatase activity appearing more sensitive to PFOA exposure than urease activity [ 15 ]. Recent research has also demonstrated that environmentally relevant concentrations of PFOS, PFOA, and perfluorobutanesulfonic acid (PFBS) can modify soil structure, soil respiration, microbial population dynamics, and enzyme activities, ultimately influencing nutrient cycling processes [ 16 ]. For instance, increases in β-glucosidase activity and litter decomposition rates have been associated with PFBS-driven shifts in microbial functioning. Collectively, these studies suggest that PFAS contamination in soil may actively alter key ecosystem processes, including carbon and phosphorus cycling. Despite increasing interest in the ecotoxicological impacts of PFAS on soils, most studies have focused on forest soils in China [ 14 ] or temperate European soils, such as Albic Luvisols from Germany [ 16 ]. This leaves a critical gap in understanding PFAS effects in Mediterranean and arid/semiarid agricultural soils. These regions have unique physicochemical characteristics, including low organic matter content, high pH, and coarse soil texture, which may influence PFAS behavior, bioavailability, and toxicity. Therefore, the main aim of this study was to examine the short- and long-term impacts of two PFAS, representing legacy (PFOA) and emerging (6:2 FTSA) compounds, on key soil enzyme activities involved in carbon, nitrogen, phosphorus, and sulfur cycling in Mediterranean and arid agricultural soils. We hypothesize that both PFAS will impair soil biochemical functioning and that these effects will be more pronounced and persistent in soils with low organic matter content. 2. Materials and Methods 2.1. Field study and soil sampling Two agricultural soils were collected for this study: an Alfisol (Xeralf) from the experimental field station of the regional government of Castilla-La Mancha (39°52'04"N, 4°02'37"W, Toledo, Spain) and an Aridisol (Argid) from abandoned cropland in northern Fuerteventura island (28°36'26"N, 13°54'27"W, Canary Islands, Spain) [ 17 ]. The former represents a Mediterranean soil; a climate region typically characterized by wet winters and extremely hot, dry summers, whereas the latter represents a desertification-prone arid zone [ 18 ]. Surface soil samples (< 15 cm deep) were collected and sieved (< 2 mm) prior to initiating the experiments. In this study, these soils are referred to as “Mediterranean” and “arid” soils. 2.2. Experimental setup Soils were spiked with PFOA and 6:2FTSA at nominal concentrations of 0, 10, 50, and 250 ng g ‒1 dry soil. Standard PFAS solutions (250 and 2.5 µg ml ‒1 ) were prepared in ethanol:H 2 O (50:50, v/v) and applied to 100 g of air-dried soils. After overnight ethanol evaporation, the treated soils were mixed with 400 g of clean soil to achieve the nominal PFAS concentrations. Each treatment included four replicates (80 g dry soil per replicate) placed in 100-ml polypropylene vessels. Soil moisture was adjusted to 30% (w/w), corresponding to 53% and 64% of water-holding capacity for the Mediterranean (0.57 ± 0.01 g H 2 O g ‒1 dry soil, mean ± SD) and arid soils (0.47 ± 0.02 g H 2 O g ‒1 dry soil), respectively. Vessels were incubated at 20ºC in the dark, and moisture was maintained gravimetrically. Subsamples (approx. 5 g) were collected at 3, 14, 60, and 210 days to assess short-term responses (e.g., Birch effect) and long-term impacts of PFAS contamination. Samples were stored at 4‒5ºC until required for enzyme measurements (within one week after collection). 2.3. Soil enzyme activities The activity of C- (esterase and β-glucosidase), P- (alkaline phosphomonoesterase and phosphodiesterase), N- (protease and N -acetyl-β-D-glucosaminidase), and S-acquiring (arylsulfatase) enzymes were measured in soil-water suspensions (1:25, w/v). The preparation of suspensions and enzymatic assays followed the procedures described in Sanchez-Hernandez et al. [ 19 ], except for N -acetyl-β-D-glucosaminidase and phosphodiesterase. The former was determined following Parham and Deng [ 20 ], with slight modifications for microplate format. Hydrolytic reactions were run in deep-well (700 µl) microplates. Aliquots (200 µl) of soil-water suspensions were incubated (continuous agitation) for 1h at 25ºC with 200 µl of 100 mM Na-acetate buffer (pH = 5.5) and 100 µl of 10 mM p-nitrophenyl- N -acetyl-β-D-glucosaminide. Reactions were terminated by centrifugation (2,500 rpm, 5 min, 4ºC), and supernatants (150 µl) were transferred to flat-bottom 96-well microplates containing 75 µl of 0.5 M NaOH. The p-nitrophenolate formed was measured at 405 nm against blanks (sample-free). Non-enzymatic substrate decomposition was checked under the same assay conditions, and enzyme activity was corrected. Activities were expressed as µmol of 4-nitrophenolate h ‒1 g ‒1 dry soil using calibration curves (1.5 to 50 mM of 4-nitrophenolate). Phosphodiesterase activity was determined according to the method of Acosta-Martínez and Tabatabai [ 23 ], adapted to a microplate format. Soil suspensions (200 µl) were incubated for 8 h with 200 µl of 50 mM Tris–HCl buffer (pH 8.0), 100 µl of 10 mM bis-nitrophenyl phosphate, and 1 mM sodium azide as microbial inhibitor. After incubation, reactions were terminated by centrifugation (2,500 rpm, 5 min, 4°C). A 150 µl aliquot of the supernatant was then transferred to microplate wells containing 100 µl of 0.1 M Tris–NaOH (pH 12.0), and absorbance at 405 nm was recorded. We also evaluated the microbial activity through dehydrogenase and catalase activities, which require viable microbial cells. Dehydrogenase activity was measured following the method of von Mersi and Schinner [ 21 ], and catalase activity following Trasar-Cepeda et al. [ 22 ], respectively. 2.4. Physicochemical properties of soils Soil subsamples were collected at the end of the experiment to assess PFAS-induced changes in pH, electrical conductivity (EC), total organic carbon (TOC), extractable NO 3 − , NH 4 + , and inorganic phosphate (P i ). Soil pH and EC were measured in soil-water suspensions (1:5, w/v). The suspensions were then centrifuged (10,000 g x 5 min) and filtered (0.22 µm, nylon) for P i determination [ 23 ], using a calibration curve made with NaH 2 PO 4 (0–50 µg PO 4 3− ml –1 ). Extractable NH 4 + and NO 3 − were measured colorimetrically in 2M KCl soil extracts (1:10, w/v) after 30-min orbital agitation (25 rpm, 24ºC). Ammonium was determined using the salicylate method [ 24 ], and NO 3 − using the Griess reagent with VCl 3 as reductant [ 25 ]. Calibration curves used NH 4 Cl (0–10 µg NH 4 + ml –1 ) and KNO 3 (0–2 µg NO 3 − ml –1 ). TOC was measured using the dichromate redox colorimetric method [ 26 ], with sucrose standards (0–16 mg C ml –1 ). 2.5. PFAS residue analysis Residues of PFOA and 6:2 FTSA were extracted from soil following Semerád et al. 2020 [ 27 ]. PFAS were extracted from soil using pressurized liquid extraction. Samples (2 g) were homogenized with 10 g of sea sand and processed in an automated solvent extractor. The optimal extraction conditions involved three cycles with methanol at 150°C and a pressure of 1500 psi. Following extraction, the resulting liquid was concentrated under a gentle stream of nitrogen. Afterwards, a purification step was performed using solid-phase extraction with activated carbon cartridges (Supelclean™ ENVI-Carb™). The analytes were then eluted using an acidified methanolic solution and further evaporated prior to instrumental determination. PFAS identification and quantification was performed in a liquid chromatography coupled with tandem mass spectrometry. Separation was achieved on a C18 column maintained at 40°C, using a gradient elution profile with mobile phases consisting of varying ratios of water, acetonitrile, and formic acid. The mass spectrometer operated with an electrospray ionization source in negative mode. Detection was carried out using multiple reaction monitoring, where two specific transitions were tracked for each substance. To ensure data quality, the method incorporates external calibration curves and regular analysis of solvent blanks and standard solutions to monitor for potential contamination or instrumental drift. 2.6. Data analysis Variations in basal enzyme activities in control soils were evaluated using two-way repeated-measures ANOVA (RM-ANOVA). Soil type (Mediterranean vs. arid) was the between-subjects factor, and sampling time (3, 14, 60, 210 days) the within-subjects factor, accounting for repeated non-destructive sampling. Tukey’s HSD post-hoc tests identified significant differences between times within soils and between both soil types at each time point. PFAS effects on enzyme activities were assessed using three complementary approaches: (1) Treated-Soil Quality Index (T-SQI). This numerical index was calculated according to Mijangos et al. [ 28 ]. The index was developed explicitly to evaluate the effects of external environmental factors (e.g., fertilization, pollution) on soil functioning [ 29 ]. It was calculated for each sampling time using the equation: $$\:T-SQI={10}^{\text{l}\text{o}\text{g}\:m+\:\frac{{\sum\:}_{i=1}^{n}\left(\text{log}{n}_{i}-\text{l}\text{o}\text{g}\:m\right)-{\sum\:}_{i=1}^{n}\left|\text{l}\text{o}\text{g}\:{n}_{i}-\text{l}\text{o}\text{g}\:\stackrel{-}{n}\right|}{n}}$$ where m is the mean enzyme activity of control soil (set to 100%), n is the mean value of each enzyme activity of PFAS-treated soils, calculated as the percentage of the mean activity of reference soil, and n̄ is the mean of n i values across enzymes. T-SQI scores > 100% indicate enhanced biochemical functioning, while scores < 100% indicates impairment. For each treatment group, mean T-SQI values were compared to 100% using two-tailed one-sample t -test, with Bonferroni correction. (2) Nutrient-acquiring enzyme activities. Following Ma et al. [ 30 ], nutrient specific mean enzyme activities were calculated as follows: C ‒acq = (EST + BG)/2, N ‒acq = (NAG + PRO)/2, and P ‒acq = (ALP + PDE)/2; where EST=esterase activity, BG = β-glucosidase, NAG = N -acetyl-β-D-glucosaminidase, PRO=protease, ALP=alkaline phosphomonoesterase, and PDE=phosphodiesterase. Effects of PFAS concentration were analyzed univariate ANOVAs with Welch’s correction, followed by Dunnett post hoc test ( p < 0.05). (3) Eco-enzymatic stoichiometry. The stoichiometric model [ 31 ] was used to explore whether PFAS contamination affected soil microbial nutrient limitations by calculating the vector length and angle based on the proportional enzyme activities [ 32 ]: $$\:Vector\:L=\:\sqrt{\left({x}^{2}+\:{y}^{2}\right)}$$ $$\:Vector\:A=\frac{\text{tan}\left(x,y\right)\:\times\:\:180}{\pi\:}$$ where x =(EST + BG)/(EST + BG+PRO + NAG) and y=(EST + BG)/(EST + BG+ALP + PDE). As recommended by Puissant [ 33 ], no log transformation was applied. Higher vector length values indicate stronger microbial C limitation compared to N and P; vector angle values 45º indicate P limitation. Nevertheless, recent theoretical frameworks propose a vector angle of 55º as a more reliable threshold for identifying N/P limitations on a global scale [ 34 ]. We compared the results of these two stoichiometric parameters using ANOVA with Welch’s correction, followed by Dunnett post hoc test ( p < 0.05). All statistical analyses were performed using the free-license JASP software (version 0.95.4, Netherlands, 2025). 3. Results and discussion 3.1. Basal enzyme dynamics in uncontaminated soils Control soils showed significant effects of soil type and incubation time on enzyme activities (Fig. 1 ). In general, enzyme activities were lower in the arid soil compared with the Mediterranean soil ( p < 0.001, Suppl. Table S1 ), which can be explained by the lower nutrient availability and TOC content in the arid soil (Suppl. Fig. S1 ). However, dehydrogenase and catalase activities were similar in both soil types after 3 days of incubation, likely reflecting a “Birch effect”, defined as a transient pulse of microbial activity triggered by the rewetting of dry soils [ 35 ]. This process releases a short-term flush of available carbon and nitrogen due to physical disruption of soil aggregates or the lysis of microbial cells caused by osmotic shock [ 36 ]. At day 3, both soils were likely responding to this initial “hot moment” of substrate availability, which temporarily masked differences in their underlying microbial potential. The subsequent decline in activity observed in both soil types, which was more pronounced in the arid soil, was probably driven by substrate exhaustion. The arid soil had a lower TOC (0.68%–0.94%, n = 28) compared with the Mediterranean soil (4.15–6.63%, n = 28), which would lead to a more rapid depletion of energy reserves required to maintain high levels of active microbial biomass. This C limitation likely explains the observed decrease of both dehydrogenase and catalase activities after 14 days of incubation (Fig. 1 ). Although a similar trend was observed in the Mediterranean soil, its higher TOC content allowed microbial activity to remain higher and more stable throughout the incubation period. The relative stability of the other enzyme activities over time suggests they are extracellular or abiontic enzymes, i.e., enzymes stabilized within the soil’s organo-mineral fraction [ 37 ]. Therefore, although nutrient depletion occurred in both soils after 210 days, these enzymes remained active while associated with organo-mineral complexes, even though viable microbial populations declined due to reduced nutrient availability. In fact, correlations between extracellular enzyme activities and dehydrogenase (or catalase) activity do not necessarily imply a mechanistic link between living cells in soil and extracellular enzyme production [ 35 ]. Nevertheless, in our study, only catalase activity positively correlated with BG ( r = 0.55, p < 0.05, Pearson’s correlation) and NAG activities ( r = 0.58), and dehydrogenase activity correlated with NAG ( r = 0.65, p < 0.05) in the Mediterranean soil. In the arid soil, dehydrogenase activity correlated with PRO ( r = 0.82, p < 0.05), while catalase and NAG activities were highly correlated ( r = 0.62, p < 0.05) in the arid soil (Suppl. Fig. S2). These observations support the idea that the pulse of microbial activity induced by soil moisture at the beginning of incubation released extracellular enzymes, which were subsequently stabilized in the organo-mineral fraction, resulting in their long-term persistence [ 37 ]. 3.2. Effects of PFAS on soil enzyme activities Soil health assessment in response to pollutants increasingly relies on the integration of multiple biochemical indicators to capture the complexity of microbial functional diversity. In this context, the T-SQI provides a robust numerical tool for quantifying changes in soil functioning relative to a reference, non-polluted soil [ 28 ]. The index integrates both the magnitude of biochemical change and the evenness of enzyme responses, making it especially sensitive to non-target pollutant effects. Several studies have used the T-SQI to assess the impact of contaminants on soil microbial functioning. For example, T-SQI values were negatively correlated with concentrations of various pesticides (fungicides, insecticides, and herbicides) [ 29 ]. Likewise, the index discriminated adverse effects of the organophosphorus insecticide chlorpyrifos on Andisols, where soil functionality dropped to approximately 41% of control levels at recommended application rates [ 19 ]. The index has been also applied to emerging contaminants such as nanomaterials. For instance, polyaniline nanorods caused consistent dose-dependent decrease in T-SQI, reflecting reduced microbial functional diversity [ 38 ]. Furthermore, Drenning et al. [ 39 ] adapted this index to track the functional recovery of soils contaminated with DDT and its metabolites during remediation, demonstrating the versatility of the index in capturing both degradation and restoration processes. In our study, integrating multiple enzyme activities involved in C, N, P, and S cycling into the T-SQI framework demonstrated that environmentally relevant concentrations of PFOA and 6:2 FTSA exerted significant negative effects on the arid soil, with T-SQI scores falling below 70% (Fig. 2 ). These effects occurred regardless of PFAS type or concentration, and no clear dose-response pattern was observed across the incubation period. In a second approach, we assessed the impact PFAS impact on nutrient-acquiring enzyme groups. PFAS significant inhibited of C- and P-acquiring enzymes in the arid soil, with the strongest inhibition caused by the fluorotelomer at 50 and 250 ng g –1 (Fig. 3 ). Percentages of activity inhibition varied from 16.5% to 49.1% for EST activity, and from 27.2% to 73.3% for BG activity. Inhibition of ALP activity ranged from 40.0% to 81.7%, whereas PDE inhibition ranged from 15.3% to 22.5%. These inhibitory responses were particularly evident in the long term (210 d) for ALP activity. Our findings agree with previous studies reporting inhibition of phosphatase activity following PFAS exposure. For example, significant inhibition of ALP activity was found in soils treated with different NPK fertilization conditions and contaminated with PFOA [ 15 ]. Enzyme inhibition was also observed at high concentrations of PFOA (75–960 µg g –1 ) after 7 d in unfertilized soil or after 28 d in fertilized soils. Accordingly, phosphatase activity has been proposed by Zhang et al. [ 40 ] as a sensitive biomarker of PFOA exposure. They reported significant inhibition of phosphatase activity across six PFOA contamination levels (10 to 1,000 µg g –1 ), which became more pronounced as incubation progressed up to day 23. Likewise, ALP activity was significantly inhibited by 500 µg kg –1 PFOA after three years, even at soil depths of 20–40 cm [ 41 ]. However, the PFAS concentrations used in these studies were considerably higher than those used in our work (10–250 ng g –1 ). Thus, our findings suggest that C- and P-acquiring enzymes can serve as sensitive indicators of PFAS exposure in agricultural soils receiving biosolids as an organic fertilizer [ 5 ]. Nevertheless, these biochemical indicators seem to be particularly useful in soils with low organic matter content, such as arid soil used in our study. This may explain the absence of a response in enzyme activities in the Mediterranean soil (Fig. 3 ), supporting the well-established role of soil organic matter as a primary PFAS sorbent that reduces bioavailability and toxicity [ 5 , 42 ]. 3.3. PFAS effects on eco-enzymatic stoichiometry Eco-enzymatic stoichiometry provides an integrated perspective on microbial nutrient limitations by relating extracellular enzyme activities to microbial resource acquisition strategies [ 32 ]. These limitations are quantified via calculation of vector length and vector angle. In our study, both parameters showed minimal variations in PFAS-treated Mediterranean soil compared with controls, except at 60 d, when 6:2 FTSA exposure caused a significant ( p < 0.05, Dunnett post hoc test) decrease in vector length coupled with an increase in vector angle (Fig. 4 ). This pattern indicates a temporary shift toward lower microbial C limitation and greater P limitation. Conversely, significant inhibition of vector length was observed in the arid soil treated with both PFAS after 210 days, indicating microbial C limitation, along with a decrease in vector angle suggesting a shift towards N limitation (Fig. 5 ). Correlations between available nutrients (P i , NH 4 + , and NO 3 − ) and these stoichiometric parameters revealed a significant negative relationship ( r =-0.57, p < 0.05, Pearson’s correlation) between vector length and P i , while a positive relationship was observed ( r = 0.58, p < 0.05, Pearson’s correlation) between vector angle and P i (Suppl. Fig. S3). These findings suggest a dependence of available P i -acquiring enzyme production on available P i , supporting the substrate stimulation theory whereby production of extracellular enzymes is induce by the abundance and availability of the substrate [ 43 ]. Eco-enzymatic stoichiometry and vector analysis have moved from a general framework for interpreting microbial resource allocation [ 32 , 44 ] to a practical tool used in contaminated soils to infer whether pollutants shift microbial demand toward C, N, or P acquisition. The most consistent evidence for this comes from heavy metals and metal-rich mine-affected soils. Several studies have reported that metal pollution increases microbial C limitation, expressed as longer vector length or stronger relative allocation to C-acquiring enzymes [ 45 – 47 ]. Similarly, vector angle varies with metal pollution, although metals do not impose a single directional shift in vector angle as they seem to magnify pre-existing nutrient constraints that are conditioned by pH, soil depth, rhizosphere effects, and nutrient status [ 46 , 48 – 50 ]. Microplastics are another contaminant group with recurrent stoichiometric effects, although their responses are more heterogeneous than those of heavy metals. For instance, in a greenhouse study, polyethylene reduced carbon limitation in nutrient-rich soil, whereas polylactic acid increased nitrogen-acquiring enzyme activity in nutrient-poor soil, indicating that the same contaminant class can either relieve or intensify carbon and nutrient limitation depending on background fertility [ 51 ]. Under combined exposure, the interaction between microplastics and antibiotics caused a clearer shift in vector angle than single-pollutant treatments, with nitrogen limitation under single exposures but phosphorus limitation under combined treatments [ 52 ]. Therefore, microplastics seem significantly affect eco-enzymatic stoichiometry, but they do so through indirect effects on soil carbon pools, aggregation, and microbial habitat quality as much as through direct toxicity [ 51 , 53 ]. Other studies have demonstrated that organic pollutants may alter eco-enzymatic stoichiometry. For instance, the rapid biodegradation of PAHs (e.g., phenanthrene at ~ 200 mg/kg) induced an initial period of greater C limitation (increased vector length) as microbes struggle with the recalcitrance and membrane-disrupting toxicity of these pollutants [ 55 ]. In other study, atrazine-contaminated soils (100 mg/kg) also showed concentration-dependent increases in vector length and vector angle, indicating severe microbial P limitation [ 54 ]. Together, these pollutant-induced shifts in vector metrics suggest a fundamental redirection of microbial energy probably toward detoxification and survival rather than biomass accumulation. In the line with this physiological adaptation, our results also suggest that PFAS, particularly 6:2 FTSA, can fundamentally alter microbial resource allocation strategies in soils with low organic matter content. 3.4. PFAS residues in soils Concentrations of PFOA and 6:2 FTSA were measured in both soil types to verify the initial nominal concentrations of 10, 50, and 250 ng g ‒1 dry soil and to assess their variations over 210 days of incubation. Measured concentrations of PFOA closely matched the nominal values in both soils and remained stable throughout the incubation period (Fig. 6 A). Likewise, initial concentrations of 6:2 FTSA also aligned with nominal values in both soils. However, a significant decrease in 6:2 FTSA concentrations was observed by day 210, being more pronounced in the Mediterranean soil (89.7–100% decrease) than in the arid soil (49.2–100%). This dissipation coincided with the formation of perfluoroheptanoic acid (PFHpA), with concentrations ranging from 1.23 ± 0.10 to 11.2 ± 1.90 ng g –1 dry soil (mean ± SD, n = 4) in the Mediterranean soil, and from 1.02 ± 0.60 to 1.89 ± 1.23 ng g –1 dry soil in the arid soil (Fig. 6 B). The transformation of 6:2 FTSA in the environment typically yields more stable short-chain perfluorocarboxylic acids, including perfluoropentanoic acid (PFPeA), perfluorohexanoic acid (PFHxA), perfluorobutanoic acid (PFBA), and PFHpA [ 56 , 57 ], depending on environmental conditions and microbial community composition [ 58 ]. In our study, PFHpA was the only terminal PFAS detected, with higher accumulation in the Mediterranean soil, consistent with its higher microbial activity. Several studies have identified specific bacteria strains, primarily isolated from polluted environments, capable of degrading 6:2 FTSA into C4–C7 fluoroalkyl acids (Table 1). However, PFHpA has not consistently been the predominant degradation product. For example, it was not detected in diluted (1:10) aerobic sludge [ 59 ], agricultural soils [ 60 ], and cultures of the bacteria Gordonia sp. strain NB4-1Y [ 61 ], exposed to 6:2 FTSA. Likewise, Labrys portucalensis F11, an aerobic bacterium isolated from industrially contaminated sites in Portugal, degraded 6:2 FTSA after 100 days of incubation, producing 4:2 FTS as the only metabolite [ 62 ]. Additionally, in sulfur-rich media incubated for 30 days with the white-rot fungus Trametopsis cervina , PFHpA was not detected among the terminal C4‒C6 fluoroalkyl acids [ 63 ]. Similarly, the bacterium Dietzia aurantiaca J3 degraded 6:2 FTSA over 168 h of incubation, forming solely PFHxA and PFPeA as the main degradation products [ 64 ]. In contrast, PFHpA has been reported as the predominant terminal PFAS in non-diluted aerobic sludges [ 65 ], in the roots of hydroponic pumpkin ( Cucurbita maxima ) [ 66 ], and to a lesser extent in the culture of Rhodococcus jostii RHA1 [ 67 , 68 ], exposed to 6:2 FTSA. Furthermore, PFHpA was detected in AFFF-impacted soils dosed with 1.7 mg L ‒1 of 6:2 FTSA over 224 days [ 69 ] and in aerobic sediments after 90 days of incubation [ 70 ]. Biodegradation studies in PFAS-contaminated landfill leachates have also identified PFHpA as a significant degradation product [ 71 ]. Collectively, our results further support the formation of PFHpA as a primary terminal and stable PFAS resulting from 6:2 FTSA biodegradation and suggest the presence of soil microorganisms that preferentially degrade the fluorotelomer into PFHpA. Sulfur-limiting conditions seem to play a critical role in the biodegradation of sulfonated PFAS such as 6:2 FTSA, by acting as a metabolic trigger for microbial desulfonation. For example, transformation of 6:2 FTSA by Gorgonia sp. Strain NB4-1Y was highly efficient only when the fluorotelomer served as the sole added sulfur source [ 61 ]. Earlier work by Van Hamme et al. [ 72 ] also reported that sulfur-limiting conditions favored the breakdown of 6:2 FTSA by this strain. Similarly, the bacterium Dietzia aurantiaca J3 specifically used 6:2 FTSA as its sulfur source under sulfur-limiting conditions [ 64 ]. In another study, Rhodococcus jostii RHA1 degraded 99% of 6:2 FTSA within 24 h when inorganic sulfate was absent [ 68 ], and microorganisms such as Rhodococcus and Sphingomonas were shown to actively participate in the transformation of 6:2FTSA under sulfur-limiting conditions [ 69 ]. In our study, the sulfur concentrations in the Mediterranean soil (313.4 mg kg –1 dry soil, Suppl. Table S2) and arid soils (192.0 mg kg –1 ) do not fully explain the higher degradation of 6:2 FTSA observed in the Mediterranean soil, although the bioavailability of this element remains unclear. However, arylsulfatase activity in the Mediterranean soil was significantly higher after spiking with 6:2 FTSA (35.4 ± 2.0 to 41.4 ± 1.1 nmol h –1 g –1 dry soil, mean ± SEM range across treatments) compared with PFOA-spiked soils (26.3 ± 1.23 to 34.3 ± 0.77 nmol h –1 g –1 dry soil) and control soils (28.8 ± 0.5 nmol h –1 g –1 dry soil) at t = 3 days. This difference persisted after 210 days of incubation (Suppl. Fig S4). Such a marked PFAS-dependent difference in arylsulfatase activity was observed in the arid soil, which suggests that biodegradation of 6:2 FTSA may provide a sulfur source for microorganisms, irrespectively of the total sulfur concentration in the soil. 4. Conclusions This study demonstrates that environmentally relevant concentrations of PFOA and 6:2 FTSA can disrupt soil extracellular enzyme activities involved in C- and P-cycling, with particularly strong effects observed in arid soils characterized by extremely low organic matter content. While the Mediterranean Alfisol exhibited considerable resilience, the arid Aridisol experienced pronounced and persistent disruption of soil health. This was reflected by a substantial decrease in the T-SQI, which dropped below 70% of control levels regardless of PFAS type or concentration. Among the enzymes studied, those involved in carbon- and phosphorus acquisition were especially sensitive to 6:2 FTSA exposure, showing inhibition levels of up to 81.7%. These results suggest two important environmental implications. First, such hydrolases could serve as sensitive biomarkers for detecting emerging PFAS contamination in soils, increasing the environmental significance of chemical analysis of PFAS residues. Second, the observed inhibition points to a microbial metabolic limitation on C and P that arises from enzyme disruption rather than from actual nutrient depletion. Eco-enzymatic stoichiometric modeling further indicated that PFAS contamination intensified microbial carbon limitation and redirected microbial energy towards cellular maintenance and survival rather than growth. Regarding PFAS persistence, PFOA remained stable throughout the 210-day incubation period in both soil types. In contrast, 6:2 FTSA underwent microbially mediated biotransformation to PFHpA. This transformation occurred more extensively in the Mediterranean soil, likely reflecting its higher baseline microbial activity. Although the two soils differed in sulfur concentrations, this factor did not appear to explain the observed fluorotelomer degradation. However, significantly higher arylsulfatase activity was found in the 6:2 FTSA-spiked Mediterranean soils, suggesting that this S-cycling enzyme may play a role in the dissipation of 6:2 FTSA. Overall, these findings highlight the need for caution when applying potentially PFAS-contaminated organic amendments, such as municipal composts or biosolids, to agricultural soils. Such inputs may promote the long-term transformation and accumulation of stable terminal PFAS while simultaneously altering microbial functioning and soil biochemical processes. Finally, the methodological framework used in this study, including enzyme-based indices such as T-SQI and eco-enzymatic stoichiometric modelling demonstrates the value of integrating biochemical indicators into soil monitoring programs. These methodological tools can help ensure that waste-to-land management strategies do not compromise the long-term productivity and ecological stability of fragile agricultural systems. Declarations Declaration of competing interest We have nothing to declare. CRediT authorship contribution statement Juan C. Sanchez-Hernandez : Conceptualization, Writing– Original draft preparation, Writing– review & editing, Visualization, Methodology, Data curation, Resources. Natividad I. Navarro Pacheco : Methodology, Formal analysis, Writing– Reviewing and Editing. Ximena Andrade Cares : Methodology, Formal analysis. Jaroslav Semerad : Methodology, Formal analysis, Writing– Reviewing and Editing. Tomas Cajthaml : Writing– Reviewing and Editing, Validation. Mallavarapu Megharaj : Conceptualization, Writing– review & editing, Validation. Acknowledgement This work received funding from the EU Horizon 2020 research program under grant agreement No. 101037509 (SCENARIOS), and by the Johannes Amos Comenius Programme (OPJAC) (project No. CZ.02.01.01/00/22_008/0004605, Natural and Anthropogenic Georisks). JCSH also acknowledges support from a Senior Researcher Visiting Grant from the University of Castilla-La Mancha to GCER (Australia). References J.P. Reganold, J.M. Wachter, Organic agriculture in the twenty-first century, Nat. Plants 2 (2016) 15221. E. Aguilera, C. Díaz-Gaona, R. García-Laureano, C. Reyes-Palomo, G.I. Guzmán, L. Ortolani, M. Sánchez-Rodríguez, V. Rodríguez-Estévez, Agroecology for adaptation to climate change and resource depletion in the Mediterranean region. A review, Agric. Syst. 181 (2020) 102809. M.Y. Nanusha, E.E. Frøkjær, J. Søndergaard, M. Mørk Larsen, C. Schwartz Glottrup, J. Bruun Nicolaisen, M. 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NB4-1Y in relation to 6 : 2 fluorotelomer sulfonate biodegradation, Microbiology 159 (2013) 1618–1628. Table Table 1 is available in the supplementary files section Additional Declarations No competing interests reported. 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Sanchez-Hernandez","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYBACxgYILQMTSGBgYD7AwFBAWAsPkhY2IDYgbBuyFh4DvFqYZyQ/e/Cj5h4PP/8B5g8/d9jl8fOf+Sbxw2AbA1AEu8NmpJkb9hwr5pGckcAm2XsmuViy4ew2yR6D2wxAERxaEsykga7nMbjBwMbA23YgccPB3m3SDEAtQBEcWtK/STP8A2o5f4D541+glv2HeZ6Btdifx+WwHDNpxjaglgMJDNJgW9h42CC2MOBwWM+bMsnevgSgXxLbpGXbkhNnnGEztgT6hUfiBnYthu3p2yR+fEuQ4+c/fPjj2za7xP7+ww9v/Ki4Lcffj91hhg0ICxtQZHgYcAB5XBKjYBSMglEwCuAAAPnPWrSouekoAAAAAElFTkSuQmCC","orcid":"","institution":"University of Castilla-La Mancha","correspondingAuthor":true,"prefix":"","firstName":"Juan","middleName":"C.","lastName":"Sanchez-Hernandez","suffix":""},{"id":617675617,"identity":"fa301139-3709-4b8b-bb4c-fd4a7de860ca","order_by":1,"name":"Natividad I. Navarro Pacheco","email":"","orcid":"","institution":"University of Castilla-La Mancha","correspondingAuthor":false,"prefix":"","firstName":"Natividad","middleName":"I. Navarro","lastName":"Pacheco","suffix":""},{"id":617675618,"identity":"92eec437-4802-485b-8727-6c26fb262ae4","order_by":2,"name":"Ximena Andrade Cares","email":"","orcid":"","institution":"University of Castilla-La Mancha","correspondingAuthor":false,"prefix":"","firstName":"Ximena","middleName":"Andrade","lastName":"Cares","suffix":""},{"id":617675619,"identity":"036cfd6f-e25f-4d4b-9e30-c4aa950d6122","order_by":3,"name":"Jaroslav Semerad","email":"","orcid":"","institution":"Charles University, Benatská","correspondingAuthor":false,"prefix":"","firstName":"Jaroslav","middleName":"","lastName":"Semerad","suffix":""},{"id":617675620,"identity":"ce562ea6-5d83-4137-b9b6-d093a3d1a8a5","order_by":4,"name":"Tomas Cajthaml","email":"","orcid":"","institution":"Charles University, Benatská","correspondingAuthor":false,"prefix":"","firstName":"Tomas","middleName":"","lastName":"Cajthaml","suffix":""},{"id":617675621,"identity":"d5e222b7-76a2-49ee-a38c-6de54f43a36a","order_by":5,"name":"Mallavarapu Megharaj","email":"","orcid":"","institution":"University of Newcastle Australia","correspondingAuthor":false,"prefix":"","firstName":"Mallavarapu","middleName":"","lastName":"Megharaj","suffix":""}],"badges":[],"createdAt":"2026-03-27 19:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9247907/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9247907/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106403592,"identity":"223f98a0-6b2c-432a-b2d8-3bd1897304fe","added_by":"auto","created_at":"2026-04-08 09:14:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":84701,"visible":true,"origin":"","legend":"\u003cp\u003eTime-dependent variation of soil enzyme activities in control (PFAS-free) soils. Tukey plots indicate the median, the 25th and 75th percentiles (box edges), the range (whiskers), and the mean (cross). Significant differences (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) between sampling times are indicated by different letters (Two-way RM ANOVA followed by Tukey HSD \u003cem\u003epost hoc\u003c/em\u003e test, statistics in Supplementary Table S1).\u003c/p\u003e","description":"","filename":"Binder21.png","url":"https://assets-eu.researchsquare.com/files/rs-9247907/v1/8dc9355a8e7130b9c29b3720.png"},{"id":106403061,"identity":"54e2ae44-7931-476f-8065-987df72d4113","added_by":"auto","created_at":"2026-04-08 09:13:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":69549,"visible":true,"origin":"","legend":"\u003cp\u003eTime-variation of treated-soil quality index (T-SQI) in Mediterranean and arid soils spiked with PFOA and 6:2 FTSA. Horizontal dotted lines denote the reference value of control soils set to 100%. * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, ** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, *** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001 (one-sample t-test against control).\u003c/p\u003e","description":"","filename":"Binder22.png","url":"https://assets-eu.researchsquare.com/files/rs-9247907/v1/39effba82139b1c1cc972d48.png"},{"id":106403229,"identity":"603338ff-9711-4bf2-bacc-d414d1b16a67","added_by":"auto","created_at":"2026-04-08 09:13:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":104757,"visible":true,"origin":"","legend":"\u003cp\u003eTime-dependent variations of nutrient-acquiring enzyme activities in PFAS-spiked soils from Mediterranean and arid regions. Enzyme activities were grouped into three categories: C-acquiring enzymes (esterase and b-glucosidase), N-acquiring enzymes (protease and \u003cem\u003eN\u003c/em\u003e-acetyl-β-D-glucosaminidase) and P-acquiring enzymes (alkaline phosphomonoesterase and phosphodiesterase). Tukey plots indicate the median, the 25th and 75th percentiles (box edges), and the range (whiskers). Significant differences between treatments (PFAS concentrations) and control at each sampling time were detected by univariate ANOVAs (Welch’s correction) and indicated by asterisks (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, Dunnett’s \u003cem\u003epost hoc\u003c/em\u003etest).\u003c/p\u003e","description":"","filename":"Binder23.png","url":"https://assets-eu.researchsquare.com/files/rs-9247907/v1/46c9c5dcf64577b927e19bd5.png"},{"id":106230708,"identity":"855ae07a-f0c7-4ed2-b90d-79f618785240","added_by":"auto","created_at":"2026-04-06 12:32:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":59976,"visible":true,"origin":"","legend":"\u003cp\u003eA) Vector length and vector angle values of the Mediterranean soil spiked with PFOA and 6:2 FTSA at 0, 10, 50, and 250 ng g\u003csup\u003e–1\u003c/sup\u003e dry soil. Tukey plots as in Fig. 3. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, Dunnett’s \u003cem\u003epost hoc\u003c/em\u003e test. B) Pearson’s correlations between vector length and angle at each time of exposure.\u003c/p\u003e","description":"","filename":"Binder24.png","url":"https://assets-eu.researchsquare.com/files/rs-9247907/v1/b8f4f30fe1b7e5b3febed0e8.png"},{"id":106230711,"identity":"29e36d8c-202c-4dbf-86fa-19e798991893","added_by":"auto","created_at":"2026-04-06 12:32:59","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":60331,"visible":true,"origin":"","legend":"\u003cp\u003eA) Vector length and vector angle values of the arid soil spiked with PFOA and 6:2 FTSA at 0, 10, 50, and 250 ng g\u003csup\u003e–1\u003c/sup\u003e dry soil. Tukey plots as in Fig. 3. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, Dunnett’s \u003cem\u003epost hoc\u003c/em\u003e test. B) Pearson’s correlations between vector length and angle at each time of exposure.\u003c/p\u003e","description":"","filename":"Binder25.png","url":"https://assets-eu.researchsquare.com/files/rs-9247907/v1/1e192054c0d97942169caec3.png"},{"id":106230712,"identity":"e376735d-d0cf-476d-ba50-d55bd902efe6","added_by":"auto","created_at":"2026-04-06 12:32:59","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":67630,"visible":true,"origin":"","legend":"\u003cp\u003eA) Measured mean (± SD, n=4) concentrations of PFOA in the Mediterranean and arid soils spiked with nominal concentrations of 10, 50, and 250 ng g\u003csup\u003e–1\u003c/sup\u003e dry mass at \u003cem\u003et\u003c/em\u003e=0 and after 210 days of soil incubation. B) Mean (± SD, n=4) concentrations of 6:2 FTSA, and its decomposed terminal PFHpA, after 210 days of incubation.\u003c/p\u003e","description":"","filename":"Binder26.png","url":"https://assets-eu.researchsquare.com/files/rs-9247907/v1/6f1759b809d17bfc709e0058.png"},{"id":106959688,"identity":"147d3402-c5ae-4f06-8232-54f7533151d9","added_by":"auto","created_at":"2026-04-15 09:13:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1229354,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9247907/v1/e4ad999d-cd9d-4891-a8f8-8592cda5520e.pdf"},{"id":106402983,"identity":"bf125c11-147c-4b84-8f80-ec857ddc4198","added_by":"auto","created_at":"2026-04-08 09:13:18","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1439406,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformationPFASToledoFuerteventura.docx","url":"https://assets-eu.researchsquare.com/files/rs-9247907/v1/d1e230c128b466ec88665025.docx"},{"id":106230706,"identity":"9b5fbffa-eda0-4edf-ac78-7379f2ced46d","added_by":"auto","created_at":"2026-04-06 12:32:59","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":156485,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9247907/v1/d921a873ad4ac0b18439d386.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Soil enzyme dynamics in arid and Mediterranean soils exposed to environmentally relevant PFAS concentrations","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSustainable agriculture promotes the use of organic amendments such as composts and biosolids as a strategy to enhance soil fertility and crop productivity [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This practice is particularly recommended in regions characterized by low soil organic matter content, including Mediterranean areas and arid environments [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, the application of these organic amendments may pose long-term environmental and human health risks due to contaminants that may be present in reclaimed wastewater, municipal composts, and biosolids [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Among these contaminants, per- and polyfluoroalkyl substances (PFAS) are frequently detected in such materials [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. PFAS are used extensively in industrial, commercial, and consumer products, including food packaging, waterproof textiles, cosmetics, paints, non-stick cookware, papermaking, oil production, mining, metal plating, electronics, and fire-fighting foams [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Their high chemical stability and resistance to environmental degradation have resulted in widespread contamination of ecosystems, including remote regions [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Among the numerous PFAS compounds, perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) are the most frequently detected PFAS in many environmental compartments. Despite their inclusion in the Stockholm Convention on Persistent Organic Pollutants, which has led to global restrictions on their production and use, both chemicals continue to be detected in sewage sludges. Reported concentrations range from 1 to 5,383 ng g\u003csup\u003e‒1\u003c/sup\u003e for PFOA, and from 0.5 to 4,780 ng g\u003csup\u003e‒1\u003c/sup\u003e for PFOS [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Consequently, agricultural soils amended with biosolids often contain substantial PFAS loads, with concentrations reaching to 2,531 ng g\u003csup\u003e‒1\u003c/sup\u003e for PFOA and 5,500 ng g\u003csup\u003e‒1\u003c/sup\u003e for PFOS [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn response to regulatory actions driven by their high environmental persistence, bioaccumulation potential, and chronic toxicity, industries have introduced emerging PFAS alternatives characterized by structural modifications. These include shorter fluorinated carbon chains, the incorporation of oxygen bridges, or the partial substitution of fluorine atoms with hydrogen or other halogens, with the aim of reducing environmental persistence and toxicity [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. One example of these emerging PFAS is 6:2 fluorotelomer sulfonic acid (6:2 FTSA), a widely used substitute for PFOS that is now also detected in wastewater treatment plants and biosolids [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Moreover, recent studies reveal that many emerging PFAS exhibit toxicity comparable to those of legacy PFAS, raising concerns about their long-term environmental and health impacts [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough agricultural soils represent major sinks for PFAS, knowledge about their ecological impacts on soil functioning remains limited. Nevertheless, several studies have shown that PFAS can alter soil physicochemical and biological properties. For example, PFOS and 6:2 FTSA have been shown to affect bacterial richness, diversity, and functional capabilities in PFAS-spiked soils, with long-chain PFAS exerting stronger effects than short-chain analogues [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Similarly, PFOA has been reported to influence soil microbial and enzymatic activity depending on the fertilization regime, alkaline phosphatase activity appearing more sensitive to PFOA exposure than urease activity [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Recent research has also demonstrated that environmentally relevant concentrations of PFOS, PFOA, and perfluorobutanesulfonic acid (PFBS) can modify soil structure, soil respiration, microbial population dynamics, and enzyme activities, ultimately influencing nutrient cycling processes [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. For instance, increases in β-glucosidase activity and litter decomposition rates have been associated with PFBS-driven shifts in microbial functioning. Collectively, these studies suggest that PFAS contamination in soil may actively alter key ecosystem processes, including carbon and phosphorus cycling.\u003c/p\u003e \u003cp\u003eDespite increasing interest in the ecotoxicological impacts of PFAS on soils, most studies have focused on forest soils in China [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] or temperate European soils, such as Albic Luvisols from Germany [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This leaves a critical gap in understanding PFAS effects in Mediterranean and arid/semiarid agricultural soils. These regions have unique physicochemical characteristics, including low organic matter content, high pH, and coarse soil texture, which may influence PFAS behavior, bioavailability, and toxicity. Therefore, the main aim of this study was to examine the short- and long-term impacts of two PFAS, representing legacy (PFOA) and emerging (6:2 FTSA) compounds, on key soil enzyme activities involved in carbon, nitrogen, phosphorus, and sulfur cycling in Mediterranean and arid agricultural soils. We hypothesize that both PFAS will impair soil biochemical functioning and that these effects will be more pronounced and persistent in soils with low organic matter content.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Field study and soil sampling\u003c/h2\u003e \u003cp\u003eTwo agricultural soils were collected for this study: an Alfisol (Xeralf) from the experimental field station of the regional government of Castilla-La Mancha (39\u0026deg;52'04\"N, 4\u0026deg;02'37\"W, Toledo, Spain) and an Aridisol (Argid) from abandoned cropland in northern Fuerteventura island (28\u0026deg;36'26\"N, 13\u0026deg;54'27\"W, Canary Islands, Spain) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The former represents a Mediterranean soil; a climate region typically characterized by wet winters and extremely hot, dry summers, whereas the latter represents a desertification-prone arid zone [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Surface soil samples (\u0026lt;\u0026thinsp;15 cm deep) were collected and sieved (\u0026lt;\u0026thinsp;2 mm) prior to initiating the experiments. In this study, these soils are referred to as \u0026ldquo;Mediterranean\u0026rdquo; and \u0026ldquo;arid\u0026rdquo; soils.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Experimental setup\u003c/h2\u003e \u003cp\u003eSoils were spiked with PFOA and 6:2FTSA at nominal concentrations of 0, 10, 50, and 250 ng g\u003csup\u003e‒1\u003c/sup\u003e dry soil. Standard PFAS solutions (250 and 2.5 \u0026micro;g ml\u003csup\u003e‒1\u003c/sup\u003e) were prepared in ethanol:H\u003csub\u003e2\u003c/sub\u003eO (50:50, v/v) and applied to 100 g of air-dried soils. After overnight ethanol evaporation, the treated soils were mixed with 400 g of clean soil to achieve the nominal PFAS concentrations. Each treatment included four replicates (80 g dry soil per replicate) placed in 100-ml polypropylene vessels. Soil moisture was adjusted to 30% (w/w), corresponding to 53% and 64% of water-holding capacity for the Mediterranean (0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01 g H\u003csub\u003e2\u003c/sub\u003eO g\u003csup\u003e‒1\u003c/sup\u003e dry soil, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) and arid soils (0.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 g H\u003csub\u003e2\u003c/sub\u003eO g\u003csup\u003e‒1\u003c/sup\u003e dry soil), respectively. Vessels were incubated at 20\u0026ordm;C in the dark, and moisture was maintained gravimetrically. Subsamples (approx. 5 g) were collected at 3, 14, 60, and 210 days to assess short-term responses (e.g., Birch effect) and long-term impacts of PFAS contamination. Samples were stored at 4‒5\u0026ordm;C until required for enzyme measurements (within one week after collection).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Soil enzyme activities\u003c/h2\u003e \u003cp\u003eThe activity of C- (esterase and β-glucosidase), P- (alkaline phosphomonoesterase and phosphodiesterase), N- (protease and \u003cem\u003eN\u003c/em\u003e-acetyl-β-D-glucosaminidase), and S-acquiring (arylsulfatase) enzymes were measured in soil-water suspensions (1:25, w/v). The preparation of suspensions and enzymatic assays followed the procedures described in Sanchez-Hernandez et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], except for \u003cem\u003eN\u003c/em\u003e-acetyl-β-D-glucosaminidase and phosphodiesterase. The former was determined following Parham and Deng [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], with slight modifications for microplate format. Hydrolytic reactions were run in deep-well (700 \u0026micro;l) microplates. Aliquots (200 \u0026micro;l) of soil-water suspensions were incubated (continuous agitation) for 1h at 25\u0026ordm;C with 200 \u0026micro;l of 100 mM Na-acetate buffer (pH\u0026thinsp;=\u0026thinsp;5.5) and 100 \u0026micro;l of 10 mM p-nitrophenyl-\u003cem\u003eN\u003c/em\u003e-acetyl-β-D-glucosaminide. Reactions were terminated by centrifugation (2,500 rpm, 5 min, 4\u0026ordm;C), and supernatants (150 \u0026micro;l) were transferred to flat-bottom 96-well microplates containing 75 \u0026micro;l of 0.5 M NaOH. The p-nitrophenolate formed was measured at 405 nm against blanks (sample-free). Non-enzymatic substrate decomposition was checked under the same assay conditions, and enzyme activity was corrected. Activities were expressed as \u0026micro;mol of 4-nitrophenolate h\u003csup\u003e‒1\u003c/sup\u003e g\u003csup\u003e‒1\u003c/sup\u003e dry soil using calibration curves (1.5 to 50 mM of 4-nitrophenolate). Phosphodiesterase activity was determined according to the method of Acosta-Mart\u0026iacute;nez and Tabatabai [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], adapted to a microplate format. Soil suspensions (200 \u0026micro;l) were incubated for 8 h with 200 \u0026micro;l of 50 mM Tris\u0026ndash;HCl buffer (pH 8.0), 100 \u0026micro;l of 10 mM bis-nitrophenyl phosphate, and 1 mM sodium azide as microbial inhibitor. After incubation, reactions were terminated by centrifugation (2,500 rpm, 5 min, 4\u0026deg;C). A 150 \u0026micro;l aliquot of the supernatant was then transferred to microplate wells containing 100 \u0026micro;l of 0.1 M Tris\u0026ndash;NaOH (pH 12.0), and absorbance at 405 nm was recorded.\u003c/p\u003e \u003cp\u003eWe also evaluated the microbial activity through dehydrogenase and catalase activities, which require viable microbial cells. Dehydrogenase activity was measured following the method of von Mersi and Schinner [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and catalase activity following Trasar-Cepeda et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Physicochemical properties of soils\u003c/h2\u003e \u003cp\u003eSoil subsamples were collected at the end of the experiment to assess PFAS-induced changes in pH, electrical conductivity (EC), total organic carbon (TOC), extractable NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, and inorganic phosphate (P\u003csub\u003ei\u003c/sub\u003e). Soil pH and EC were measured in soil-water suspensions (1:5, w/v). The suspensions were then centrifuged (10,000 g x 5 min) and filtered (0.22 \u0026micro;m, nylon) for P\u003csub\u003ei\u003c/sub\u003e determination [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], using a calibration curve made with NaH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e (0\u0026ndash;50 \u0026micro;g PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u0026minus;\u003c/sup\u003e ml\u003csup\u003e\u0026ndash;1\u003c/sup\u003e). Extractable NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e were measured colorimetrically in 2M KCl soil extracts (1:10, w/v) after 30-min orbital agitation (25 rpm, 24\u0026ordm;C). Ammonium was determined using the salicylate method [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e using the Griess reagent with VCl\u003csub\u003e3\u003c/sub\u003e as reductant [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Calibration curves used NH\u003csub\u003e4\u003c/sub\u003eCl (0\u0026ndash;10 \u0026micro;g NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e ml\u003csup\u003e\u0026ndash;1\u003c/sup\u003e) and KNO\u003csub\u003e3\u003c/sub\u003e (0\u0026ndash;2 \u0026micro;g NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e ml\u003csup\u003e\u0026ndash;1\u003c/sup\u003e). TOC was measured using the dichromate redox colorimetric method [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], with sucrose standards (0\u0026ndash;16 mg C ml\u003csup\u003e\u0026ndash;1\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. PFAS residue analysis\u003c/h2\u003e \u003cp\u003eResidues of PFOA and 6:2 FTSA were extracted from soil following Semer\u0026aacute;d et al. 2020 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. PFAS were extracted from soil using pressurized liquid extraction. Samples (2 g) were homogenized with 10 g of sea sand and processed in an automated solvent extractor. The optimal extraction conditions involved three cycles with methanol at 150\u0026deg;C and a pressure of 1500 psi. Following extraction, the resulting liquid was concentrated under a gentle stream of nitrogen. Afterwards, a purification step was performed using solid-phase extraction with activated carbon cartridges (Supelclean\u0026trade; ENVI-Carb\u0026trade;). The analytes were then eluted using an acidified methanolic solution and further evaporated prior to instrumental determination. PFAS identification and quantification was performed in a liquid chromatography coupled with tandem mass spectrometry. Separation was achieved on a C18 column maintained at 40\u0026deg;C, using a gradient elution profile with mobile phases consisting of varying ratios of water, acetonitrile, and formic acid. The mass spectrometer operated with an electrospray ionization source in negative mode. Detection was carried out using multiple reaction monitoring, where two specific transitions were tracked for each substance. To ensure data quality, the method incorporates external calibration curves and regular analysis of solvent blanks and standard solutions to monitor for potential contamination or instrumental drift.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Data analysis\u003c/h2\u003e \u003cp\u003eVariations in basal enzyme activities in control soils were evaluated using two-way repeated-measures ANOVA (RM-ANOVA). Soil type (Mediterranean \u003cem\u003evs.\u003c/em\u003e arid) was the between-subjects factor, and sampling time (3, 14, 60, 210 days) the within-subjects factor, accounting for repeated non-destructive sampling. Tukey\u0026rsquo;s HSD post-hoc tests identified significant differences between times within soils and between both soil types at each time point.\u003c/p\u003e \u003cp\u003ePFAS effects on enzyme activities were assessed using three complementary approaches:\u003c/p\u003e \u003cp\u003e(1) Treated-Soil Quality Index (T-SQI). This numerical index was calculated according to Mijangos et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The index was developed explicitly to evaluate the effects of external environmental factors (e.g., fertilization, pollution) on soil functioning [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It was calculated for each sampling time using the equation:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:T-SQI={10}^{\\text{l}\\text{o}\\text{g}\\:m+\\:\\frac{{\\sum\\:}_{i=1}^{n}\\left(\\text{log}{n}_{i}-\\text{l}\\text{o}\\text{g}\\:m\\right)-{\\sum\\:}_{i=1}^{n}\\left|\\text{l}\\text{o}\\text{g}\\:{n}_{i}-\\text{l}\\text{o}\\text{g}\\:\\stackrel{-}{n}\\right|}{n}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003em\u003c/em\u003e is the mean enzyme activity of control soil (set to 100%), \u003cem\u003en\u003c/em\u003e is the mean value of each enzyme activity of PFAS-treated soils, calculated as the percentage of the mean activity of reference soil, and \u003cem\u003en̄\u003c/em\u003e is the mean of \u003cem\u003en\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e values across enzymes. T-SQI scores\u0026thinsp;\u0026gt;\u0026thinsp;100% indicate enhanced biochemical functioning, while scores\u0026thinsp;\u0026lt;\u0026thinsp;100% indicates impairment. For each treatment group, mean T-SQI values were compared to 100% using two-tailed one-sample \u003cem\u003et\u003c/em\u003e-test, with Bonferroni correction.\u003c/p\u003e \u003cp\u003e(2) Nutrient-acquiring enzyme activities. Following Ma et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], nutrient specific mean enzyme activities were calculated as follows: \u003cem\u003eC\u003c/em\u003e‒acq = (EST\u0026thinsp;+\u0026thinsp;BG)/2, \u003cem\u003eN\u003c/em\u003e‒acq = (NAG\u0026thinsp;+\u0026thinsp;PRO)/2, and \u003cem\u003eP\u003c/em\u003e‒acq = (ALP\u0026thinsp;+\u0026thinsp;PDE)/2; where EST=esterase activity, BG\u0026thinsp;=\u0026thinsp;β-glucosidase, NAG\u0026thinsp;=\u0026thinsp;\u003cem\u003eN\u003c/em\u003e-acetyl-β-D-glucosaminidase, PRO=protease, ALP=alkaline phosphomonoesterase, and PDE=phosphodiesterase. Effects of PFAS concentration were analyzed univariate ANOVAs with Welch\u0026rsquo;s correction, followed by Dunnett \u003cem\u003epost hoc\u003c/em\u003e test (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e(3) Eco-enzymatic stoichiometry. The stoichiometric model [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] was used to explore whether PFAS contamination affected soil microbial nutrient limitations by calculating the vector length and angle based on the proportional enzyme activities [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:Vector\\:L=\\:\\sqrt{\\left({x}^{2}+\\:{y}^{2}\\right)}$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:Vector\\:A=\\frac{\\text{tan}\\left(x,y\\right)\\:\\times\\:\\:180}{\\pi\\:}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003ex\u003c/em\u003e=(EST\u0026thinsp;+\u0026thinsp;BG)/(EST\u0026thinsp;+\u0026thinsp;BG+PRO\u0026thinsp;+\u0026thinsp;NAG) and y=(EST\u0026thinsp;+\u0026thinsp;BG)/(EST\u0026thinsp;+\u0026thinsp;BG+ALP\u0026thinsp;+\u0026thinsp;PDE). As recommended by Puissant [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], no log transformation was applied. Higher vector length values indicate stronger microbial C limitation compared to N and P; vector angle values \u0026lt;\u0026thinsp;45\u0026ordm; indicate N limitation, while \u0026gt;\u0026thinsp;45\u0026ordm; indicate P limitation. Nevertheless, recent theoretical frameworks propose a vector angle of 55\u0026ordm; as a more reliable threshold for identifying N/P limitations on a global scale [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. We compared the results of these two stoichiometric parameters using ANOVA with Welch\u0026rsquo;s correction, followed by Dunnett post hoc test (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). All statistical analyses were performed using the free-license JASP software (version 0.95.4, Netherlands, 2025).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Basal enzyme dynamics in uncontaminated soils\u003c/h2\u003e \u003cp\u003eControl soils showed significant effects of soil type and incubation time on enzyme activities (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In general, enzyme activities were lower in the arid soil compared with the Mediterranean soil (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Suppl. Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), which can be explained by the lower nutrient availability and TOC content in the arid soil (Suppl. Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). However, dehydrogenase and catalase activities were similar in both soil types after 3 days of incubation, likely reflecting a \u0026ldquo;Birch effect\u0026rdquo;, defined as a transient pulse of microbial activity triggered by the rewetting of dry soils [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This process releases a short-term flush of available carbon and nitrogen due to physical disruption of soil aggregates or the lysis of microbial cells caused by osmotic shock [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. At day 3, both soils were likely responding to this initial \u0026ldquo;hot moment\u0026rdquo; of substrate availability, which temporarily masked differences in their underlying microbial potential. The subsequent decline in activity observed in both soil types, which was more pronounced in the arid soil, was probably driven by substrate exhaustion. The arid soil had a lower TOC (0.68%\u0026ndash;0.94%, n\u0026thinsp;=\u0026thinsp;28) compared with the Mediterranean soil (4.15\u0026ndash;6.63%, n\u0026thinsp;=\u0026thinsp;28), which would lead to a more rapid depletion of energy reserves required to maintain high levels of active microbial biomass. This C limitation likely explains the observed decrease of both dehydrogenase and catalase activities after 14 days of incubation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Although a similar trend was observed in the Mediterranean soil, its higher TOC content allowed microbial activity to remain higher and more stable throughout the incubation period.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe relative stability of the other enzyme activities over time suggests they are extracellular or abiontic enzymes, i.e., enzymes stabilized within the soil\u0026rsquo;s organo-mineral fraction [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Therefore, although nutrient depletion occurred in both soils after 210 days, these enzymes remained active while associated with organo-mineral complexes, even though viable microbial populations declined due to reduced nutrient availability. In fact, correlations between extracellular enzyme activities and dehydrogenase (or catalase) activity do not necessarily imply a mechanistic link between living cells in soil and extracellular enzyme production [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Nevertheless, in our study, only catalase activity positively correlated with BG (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.55, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Pearson\u0026rsquo;s correlation) and NAG activities (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.58), and dehydrogenase activity correlated with NAG (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.65, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the Mediterranean soil. In the arid soil, dehydrogenase activity correlated with PRO (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.82, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while catalase and NAG activities were highly correlated (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.62, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the arid soil (Suppl. Fig. S2). These observations support the idea that the pulse of microbial activity induced by soil moisture at the beginning of incubation released extracellular enzymes, which were subsequently stabilized in the organo-mineral fraction, resulting in their long-term persistence [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Effects of PFAS on soil enzyme activities\u003c/h2\u003e \u003cp\u003eSoil health assessment in response to pollutants increasingly relies on the integration of multiple biochemical indicators to capture the complexity of microbial functional diversity. In this context, the T-SQI provides a robust numerical tool for quantifying changes in soil functioning relative to a reference, non-polluted soil [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The index integrates both the magnitude of biochemical change and the evenness of enzyme responses, making it especially sensitive to non-target pollutant effects.\u003c/p\u003e \u003cp\u003eSeveral studies have used the T-SQI to assess the impact of contaminants on soil microbial functioning. For example, T-SQI values were negatively correlated with concentrations of various pesticides (fungicides, insecticides, and herbicides) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Likewise, the index discriminated adverse effects of the organophosphorus insecticide chlorpyrifos on Andisols, where soil functionality dropped to approximately 41% of control levels at recommended application rates [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The index has been also applied to emerging contaminants such as nanomaterials. For instance, polyaniline nanorods caused consistent dose-dependent decrease in T-SQI, reflecting reduced microbial functional diversity [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Furthermore, Drenning et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] adapted this index to track the functional recovery of soils contaminated with DDT and its metabolites during remediation, demonstrating the versatility of the index in capturing both degradation and restoration processes. In our study, integrating multiple enzyme activities involved in C, N, P, and S cycling into the T-SQI framework demonstrated that environmentally relevant concentrations of PFOA and 6:2 FTSA exerted significant negative effects on the arid soil, with T-SQI scores falling below 70% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These effects occurred regardless of PFAS type or concentration, and no clear dose-response pattern was observed across the incubation period.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn a second approach, we assessed the impact PFAS impact on nutrient-acquiring enzyme groups. PFAS significant inhibited of C- and P-acquiring enzymes in the arid soil, with the strongest inhibition caused by the fluorotelomer at 50 and 250 ng g\u003csup\u003e\u0026ndash;1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Percentages of activity inhibition varied from 16.5% to 49.1% for EST activity, and from 27.2% to 73.3% for BG activity. Inhibition of ALP activity ranged from 40.0% to 81.7%, whereas PDE inhibition ranged from 15.3% to 22.5%. These inhibitory responses were particularly evident in the long term (210 d) for ALP activity. Our findings agree with previous studies reporting inhibition of phosphatase activity following PFAS exposure. For example, significant inhibition of ALP activity was found in soils treated with different NPK fertilization conditions and contaminated with PFOA [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Enzyme inhibition was also observed at high concentrations of PFOA (75\u0026ndash;960 \u0026micro;g g\u003csup\u003e\u0026ndash;1\u003c/sup\u003e) after 7 d in unfertilized soil or after 28 d in fertilized soils. Accordingly, phosphatase activity has been proposed by Zhang et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] as a sensitive biomarker of PFOA exposure. They reported significant inhibition of phosphatase activity across six PFOA contamination levels (10 to 1,000 \u0026micro;g g\u003csup\u003e\u0026ndash;1\u003c/sup\u003e), which became more pronounced as incubation progressed up to day 23. Likewise, ALP activity was significantly inhibited by 500 \u0026micro;g kg\u003csup\u003e\u0026ndash;1\u003c/sup\u003e PFOA after three years, even at soil depths of 20\u0026ndash;40 cm [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. However, the PFAS concentrations used in these studies were considerably higher than those used in our work (10\u0026ndash;250 ng g\u003csup\u003e\u0026ndash;1\u003c/sup\u003e). Thus, our findings suggest that C- and P-acquiring enzymes can serve as sensitive indicators of PFAS exposure in agricultural soils receiving biosolids as an organic fertilizer [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Nevertheless, these biochemical indicators seem to be particularly useful in soils with low organic matter content, such as arid soil used in our study. This may explain the absence of a response in enzyme activities in the Mediterranean soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), supporting the well-established role of soil organic matter as a primary PFAS sorbent that reduces bioavailability and toxicity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. PFAS effects on eco-enzymatic stoichiometry\u003c/h2\u003e \u003cp\u003eEco-enzymatic stoichiometry provides an integrated perspective on microbial nutrient limitations by relating extracellular enzyme activities to microbial resource acquisition strategies [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. These limitations are quantified via calculation of vector length and vector angle. In our study, both parameters showed minimal variations in PFAS-treated Mediterranean soil compared with controls, except at 60 d, when 6:2 FTSA exposure caused a significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Dunnett post hoc test) decrease in vector length coupled with an increase in vector angle (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This pattern indicates a temporary shift toward lower microbial C limitation and greater P limitation. Conversely, significant inhibition of vector length was observed in the arid soil treated with both PFAS after 210 days, indicating microbial C limitation, along with a decrease in vector angle suggesting a shift towards N limitation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Correlations between available nutrients (P\u003csub\u003ei\u003c/sub\u003e, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e) and these stoichiometric parameters revealed a significant negative relationship (\u003cem\u003er\u003c/em\u003e=-0.57, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Pearson\u0026rsquo;s correlation) between vector length and P\u003csub\u003ei\u003c/sub\u003e, while a positive relationship was observed (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.58, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Pearson\u0026rsquo;s correlation) between vector angle and P\u003csub\u003ei\u003c/sub\u003e (Suppl. Fig. S3). These findings suggest a dependence of available P\u003csub\u003ei\u003c/sub\u003e-acquiring enzyme production on available P\u003csub\u003ei\u003c/sub\u003e, supporting the substrate stimulation theory whereby production of extracellular enzymes is induce by the abundance and availability of the substrate [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eEco-enzymatic stoichiometry and vector analysis have moved from a general framework for interpreting microbial resource allocation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] to a practical tool used in contaminated soils to infer whether pollutants shift microbial demand toward C, N, or P acquisition. The most consistent evidence for this comes from heavy metals and metal-rich mine-affected soils. Several studies have reported that metal pollution increases microbial C limitation, expressed as longer vector length or stronger relative allocation to C-acquiring enzymes [\u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Similarly, vector angle varies with metal pollution, although metals do not impose a single directional shift in vector angle as they seem to magnify pre-existing nutrient constraints that are conditioned by pH, soil depth, rhizosphere effects, and nutrient status [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Microplastics are another contaminant group with recurrent stoichiometric effects, although their responses are more heterogeneous than those of heavy metals. For instance, in a greenhouse study, polyethylene reduced carbon limitation in nutrient-rich soil, whereas polylactic acid increased nitrogen-acquiring enzyme activity in nutrient-poor soil, indicating that the same contaminant class can either relieve or intensify carbon and nutrient limitation depending on background fertility [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Under combined exposure, the interaction between microplastics and antibiotics caused a clearer shift in vector angle than single-pollutant treatments, with nitrogen limitation under single exposures but phosphorus limitation under combined treatments [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Therefore, microplastics seem significantly affect eco-enzymatic stoichiometry, but they do so through indirect effects on soil carbon pools, aggregation, and microbial habitat quality as much as through direct toxicity [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Other studies have demonstrated that organic pollutants may alter eco-enzymatic stoichiometry. For instance, the rapid biodegradation of PAHs (e.g., phenanthrene at ~\u0026thinsp;200 mg/kg) induced an initial period of greater C limitation (increased vector length) as microbes struggle with the recalcitrance and membrane-disrupting toxicity of these pollutants [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. In other study, atrazine-contaminated soils (100 mg/kg) also showed concentration-dependent increases in vector length and vector angle, indicating severe microbial P limitation [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Together, these pollutant-induced shifts in vector metrics suggest a fundamental redirection of microbial energy probably toward detoxification and survival rather than biomass accumulation. In the line with this physiological adaptation, our results also suggest that PFAS, particularly 6:2 FTSA, can fundamentally alter microbial resource allocation strategies in soils with low organic matter content.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4. PFAS residues in soils\u003c/h2\u003e \u003cp\u003eConcentrations of PFOA and 6:2 FTSA were measured in both soil types to verify the initial nominal concentrations of 10, 50, and 250 ng g\u003csup\u003e‒1\u003c/sup\u003e dry soil and to assess their variations over 210 days of incubation. Measured concentrations of PFOA closely matched the nominal values in both soils and remained stable throughout the incubation period (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Likewise, initial concentrations of 6:2 FTSA also aligned with nominal values in both soils. However, a significant decrease in 6:2 FTSA concentrations was observed by day 210, being more pronounced in the Mediterranean soil (89.7\u0026ndash;100% decrease) than in the arid soil (49.2\u0026ndash;100%). This dissipation coincided with the formation of perfluoroheptanoic acid (PFHpA), with concentrations ranging from 1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10 to 11.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90 ng g\u003csup\u003e\u0026ndash;1\u003c/sup\u003e dry soil (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;4) in the Mediterranean soil, and from 1.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60 to 1.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23 ng g\u003csup\u003e\u0026ndash;1\u003c/sup\u003e dry soil in the arid soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe transformation of 6:2 FTSA in the environment typically yields more stable short-chain perfluorocarboxylic acids, including perfluoropentanoic acid (PFPeA), perfluorohexanoic acid (PFHxA), perfluorobutanoic acid (PFBA), and PFHpA [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], depending on environmental conditions and microbial community composition [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. In our study, PFHpA was the only terminal PFAS detected, with higher accumulation in the Mediterranean soil, consistent with its higher microbial activity. Several studies have identified specific bacteria strains, primarily isolated from polluted environments, capable of degrading 6:2 FTSA into C4\u0026ndash;C7 fluoroalkyl acids (Table\u0026nbsp;1). However, PFHpA has not consistently been the predominant degradation product. For example, it was not detected in diluted (1:10) aerobic sludge [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], agricultural soils [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], and cultures of the bacteria \u003cem\u003eGordonia sp.\u003c/em\u003e strain NB4-1Y [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], exposed to 6:2 FTSA. Likewise, \u003cem\u003eLabrys portucalensis\u003c/em\u003e F11, an aerobic bacterium isolated from industrially contaminated sites in Portugal, degraded 6:2 FTSA after 100 days of incubation, producing 4:2 FTS as the only metabolite [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Additionally, in sulfur-rich media incubated for 30 days with the white-rot fungus \u003cem\u003eTrametopsis cervina\u003c/em\u003e, PFHpA was not detected among the terminal C4‒C6 fluoroalkyl acids [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Similarly, the bacterium \u003cem\u003eDietzia aurantiaca\u003c/em\u003e J3 degraded 6:2 FTSA over 168 h of incubation, forming solely PFHxA and PFPeA as the main degradation products [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. In contrast, PFHpA has been reported as the predominant terminal PFAS in non-diluted aerobic sludges [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], in the roots of hydroponic pumpkin (\u003cem\u003eCucurbita maxima\u003c/em\u003e) [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], and to a lesser extent in the culture of \u003cem\u003eRhodococcus jostii\u003c/em\u003e RHA1 [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], exposed to 6:2 FTSA. Furthermore, PFHpA was detected in AFFF-impacted soils dosed with 1.7 mg L\u003csup\u003e‒1\u003c/sup\u003e of 6:2 FTSA over 224 days [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] and in aerobic sediments after 90 days of incubation [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Biodegradation studies in PFAS-contaminated landfill leachates have also identified PFHpA as a significant degradation product [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Collectively, our results further support the formation of PFHpA as a primary terminal and stable PFAS resulting from 6:2 FTSA biodegradation and suggest the presence of soil microorganisms that preferentially degrade the fluorotelomer into PFHpA.\u003c/p\u003e \u003cp\u003eSulfur-limiting conditions seem to play a critical role in the biodegradation of sulfonated PFAS such as 6:2 FTSA, by acting as a metabolic trigger for microbial desulfonation. For example, transformation of 6:2 FTSA by \u003cem\u003eGorgonia\u003c/em\u003e sp. Strain NB4-1Y was highly efficient only when the fluorotelomer served as the sole added sulfur source [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Earlier work by Van Hamme et al. [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] also reported that sulfur-limiting conditions favored the breakdown of 6:2 FTSA by this strain. Similarly, the bacterium \u003cem\u003eDietzia aurantiaca\u003c/em\u003e J3 specifically used 6:2 FTSA as its sulfur source under sulfur-limiting conditions [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. In another study, \u003cem\u003eRhodococcus jostii\u003c/em\u003e RHA1 degraded 99% of 6:2 FTSA within 24 h when inorganic sulfate was absent [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], and microorganisms such as \u003cem\u003eRhodococcus\u003c/em\u003e and \u003cem\u003eSphingomonas\u003c/em\u003e were shown to actively participate in the transformation of 6:2FTSA under sulfur-limiting conditions [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. In our study, the sulfur concentrations in the Mediterranean soil (313.4 mg kg\u003csup\u003e\u0026ndash;1\u003c/sup\u003e dry soil, Suppl. Table S2) and arid soils (192.0 mg kg\u003csup\u003e\u0026ndash;1\u003c/sup\u003e) do not fully explain the higher degradation of 6:2 FTSA observed in the Mediterranean soil, although the bioavailability of this element remains unclear. However, arylsulfatase activity in the Mediterranean soil was significantly higher after spiking with 6:2 FTSA (35.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0 to 41.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 nmol h\u003csup\u003e\u0026ndash;1\u003c/sup\u003e g\u003csup\u003e\u0026ndash;1\u003c/sup\u003e dry soil, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM range across treatments) compared with PFOA-spiked soils (26.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23 to 34.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77 nmol h\u003csup\u003e\u0026ndash;1\u003c/sup\u003e g\u003csup\u003e\u0026ndash;1\u003c/sup\u003e dry soil) and control soils (28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 nmol h\u003csup\u003e\u0026ndash;1\u003c/sup\u003e g\u003csup\u003e\u0026ndash;1\u003c/sup\u003e dry soil) at \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3 days. This difference persisted after 210 days of incubation (Suppl. Fig S4). Such a marked PFAS-dependent difference in arylsulfatase activity was observed in the arid soil, which suggests that biodegradation of 6:2 FTSA may provide a sulfur source for microorganisms, irrespectively of the total sulfur concentration in the soil.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eThis study demonstrates that environmentally relevant concentrations of PFOA and 6:2 FTSA can disrupt soil extracellular enzyme activities involved in C- and P-cycling, with particularly strong effects observed in arid soils characterized by extremely low organic matter content. While the Mediterranean Alfisol exhibited considerable resilience, the arid Aridisol experienced pronounced and persistent disruption of soil health. This was reflected by a substantial decrease in the T-SQI, which dropped below 70% of control levels regardless of PFAS type or concentration. Among the enzymes studied, those involved in carbon- and phosphorus acquisition were especially sensitive to 6:2 FTSA exposure, showing inhibition levels of up to 81.7%. These results suggest two important environmental implications. First, such hydrolases could serve as sensitive biomarkers for detecting emerging PFAS contamination in soils, increasing the environmental significance of chemical analysis of PFAS residues. Second, the observed inhibition points to a microbial metabolic limitation on C and P that arises from enzyme disruption rather than from actual nutrient depletion. Eco-enzymatic stoichiometric modeling further indicated that PFAS contamination intensified microbial carbon limitation and redirected microbial energy towards cellular maintenance and survival rather than growth. Regarding PFAS persistence, PFOA remained stable throughout the 210-day incubation period in both soil types. In contrast, 6:2 FTSA underwent microbially mediated biotransformation to PFHpA. This transformation occurred more extensively in the Mediterranean soil, likely reflecting its higher baseline microbial activity. Although the two soils differed in sulfur concentrations, this factor did not appear to explain the observed fluorotelomer degradation. However, significantly higher arylsulfatase activity was found in the 6:2 FTSA-spiked Mediterranean soils, suggesting that this S-cycling enzyme may play a role in the dissipation of 6:2 FTSA. Overall, these findings highlight the need for caution when applying potentially PFAS-contaminated organic amendments, such as municipal composts or biosolids, to agricultural soils. Such inputs may promote the long-term transformation and accumulation of stable terminal PFAS while simultaneously altering microbial functioning and soil biochemical processes. Finally, the methodological framework used in this study, including enzyme-based indices such as T-SQI and eco-enzymatic stoichiometric modelling demonstrates the value of integrating biochemical indicators into soil monitoring programs. These methodological tools can help ensure that waste-to-land management strategies do not compromise the long-term productivity and ecological stability of fragile agricultural systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have nothing to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJuan C. Sanchez-Hernandez\u003c/strong\u003e: Conceptualization, Writing– Original draft preparation, Writing– review \u0026amp; editing, Visualization, Methodology, Data curation, Resources.\u0026nbsp;\u003cstrong\u003eNatividad I. Navarro Pacheco\u003c/strong\u003e: Methodology, Formal analysis, Writing– Reviewing and Editing.\u0026nbsp;\u003cstrong\u003eXimena Andrade Cares\u003c/strong\u003e: Methodology, Formal\u0026nbsp;analysis. \u003cstrong\u003eJaroslav Semerad\u003c/strong\u003e: Methodology,\u0026nbsp;Formal analysis, Writing– Reviewing and Editing.\u0026nbsp;\u003cstrong\u003eTomas Cajthaml\u003c/strong\u003e:\u0026nbsp;Writing– Reviewing and Editing, Validation.\u0026nbsp;\u003cstrong\u003eMallavarapu Megharaj\u003c/strong\u003e:\u0026nbsp;Conceptualization, Writing– review \u0026amp; editing, Validation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work received funding from the EU Horizon 2020 research program under grant agreement No. 101037509 (SCENARIOS), and by the Johannes Amos Comenius Programme (OPJAC) (project No. CZ.02.01.01/00/22_008/0004605, Natural and Anthropogenic Georisks). JCSH also acknowledges support from a Senior Researcher Visiting Grant from the University of Castilla-La Mancha to GCER (Australia).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJ.P. Reganold, J.M. Wachter, Organic agriculture in the twenty-first century, Nat. Plants 2 (2016) 15221.\u003c/li\u003e\n\u003cli\u003eE. Aguilera, C. D\u0026iacute;az-Gaona, R. Garc\u0026iacute;a-Laureano, C. Reyes-Palomo, G.I. Guzm\u0026aacute;n, L. Ortolani, M. S\u0026aacute;nchez-Rodr\u0026iacute;guez, V. Rodr\u0026iacute;guez-Est\u0026eacute;vez, Agroecology for adaptation to climate change and resource depletion in the Mediterranean region. A review, Agric. Syst. 181 (2020) 102809.\u003c/li\u003e\n\u003cli\u003eM.Y. Nanusha, E.E. Fr\u0026oslash;kj\u0026aelig;r, J. S\u0026oslash;ndergaard, M. M\u0026oslash;rk Larsen, C. Schwartz Glottrup, J. Bruun Nicolaisen, M. 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Buck, Biotransformation potential of 6:2 fluorotelomer sulfonate (6:2 FTSA) in aerobic and anaerobic sediment, Chemosphere 154 (2016) 224\u0026ndash;230.\u003c/li\u003e\n\u003cli\u003eH. Hamid, L.Y. Li, J.R. Grace, Effect of substrate concentrations on aerobic biotransformation of 6:2 fluorotelomer sulfonate (6:2 FTS) in landfill leachate, Chemosphere 261 (2020) 128108.\u003c/li\u003e\n\u003cli\u003eJ.D. Van Hamme, E.M. Bottos, N.J. Bilbey, S.E. Brewer, Genomic and proteomic characterization of Gordonia sp. NB4-1Y in relation to 6 : 2 fluorotelomer sulfonate biodegradation, Microbiology 159 (2013) 1618\u0026ndash;1628.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1 is available in the supplementary files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-emerging-contaminants","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Emerging Contaminants](https://www.nature.com/npjemergcontam/)","snPcode":"44454","submissionUrl":"https://submission.springernature.com/new-submission/44454/3","title":"npj Emerging Contaminants","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Unsupported Journal","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"PFOA, 6:2 FTSA, soil enzymes, eco-enzymatic stoichiometry, enzymatic index, arid soils","lastPublishedDoi":"10.21203/rs.3.rs-9247907/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9247907/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigated the short- and long-term effects of perfluorooctanoic acid (PFOA) and 6:2 fluorotelomer sulfonic acid (6:2 FTSA) on the biochemical functioning of agricultural soils with contrasting organic matter content, specifically Mediterranean and arid soils. Soil samples were spiked with environmentally relevant concentrations of both PFAS (10, 50, and 250 ng g⁻\u0026sup1; dry mass) and incubated for 210 days to monitor changes in microbial and enzymatic activities. The results revealed that both PFAS significantly impaired soil biochemical functioning in the arid soil, with Treated-Soil Quality Index (T-SQI) values declining to less than 70% of control levels. Specifically, 6:2 FTSA caused significant inhibition of carbon- and phosphorus-acquiring enzymes such as β-glucosidase and alkaline phosphomonoesterase, with inhibition levels reaching up to 81.7%. In contrast, the Mediterranean soil exhibited minimal enzymatic response, which was attributed to its higher organic matter content that likely decreased PFAS bioavailability. Eco-enzymatic stoichiometric modeling further indicated that PFAS exposure increased microbial carbon limitation and altered nutrient acquisition strategies in arid soils over the long term. While PFOA concentrations remained relatively stable throughout the study, 6:2 FTSA underwent microbially mediated transformation to perfluoroheptanoic acid (PFHpA), with more pronounced dissipation occurring in the Mediterranean soil. Overall, these findings highlight the greater vulnerability of low-organic matter arid soils to both legacy and emerging PFAS, emphasize the risk of impaired nutrient cycling associated with PFAS-contaminated organic amendments, and underscore the importance of careful management of biosolids and municipal composts in dryland agricultural systems.\u003c/p\u003e","manuscriptTitle":"Soil enzyme dynamics in arid and Mediterranean soils exposed to environmentally relevant PFAS concentrations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-06 12:32:54","doi":"10.21203/rs.3.rs-9247907/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-26T02:31:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-24T14:57:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-24T02:51:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"228495699765678084129292329024377889789","date":"2026-04-14T13:35:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"24077738751378673935076326331982765998","date":"2026-04-13T08:47:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-01T14:17:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"221929339052077107761663733378727395100","date":"2026-04-01T13:44:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-31T15:42:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-30T21:34:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-30T16:49:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Emerging Contaminants","date":"2026-03-27T19:30:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-emerging-contaminants","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Emerging Contaminants](https://www.nature.com/npjemergcontam/)","snPcode":"44454","submissionUrl":"https://submission.springernature.com/new-submission/44454/3","title":"npj Emerging Contaminants","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Unsupported Journal","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8c0caa45-0ee8-4cff-8c7b-ecfb8fd45b19","owner":[],"postedDate":"April 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":65735565,"name":"Earth and environmental sciences/Biogeochemistry"},{"id":65735566,"name":"Biological sciences/Ecology"},{"id":65735567,"name":"Earth and environmental sciences/Ecology"},{"id":65735568,"name":"Earth and environmental sciences/Environmental sciences"},{"id":65735569,"name":"Biological sciences/Microbiology"}],"tags":[],"updatedAt":"2026-04-26T02:38:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-06 12:32:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9247907","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9247907","identity":"rs-9247907","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}