Exploring Organic Matter, Soil Enzymes, and Fungal Communities Under Land-Use Intensification in the Argentine Pampas

Abstract

Intensive land use in the Argentine Pampas has led to soil degradation, yet links between soil organic matter (SOM) composition, enzyme activity, and fungal communities remain unclear. This study compared contrasting ecoregions and land uses: pristine (PI), pasture (PA), crop rotation with cover crops (RO), and monoculture (MO). Infrared spectra showed that PI soils in Anguil had higher absorbance in hydroxyl/amine (3400 cm⁻¹: 0.90 ± 0.08) and carbonyl (1750 cm⁻¹: 0.52 ± 0.12) bands than MO soils (0.47 ± 0.30 and 0.35 ± 0.06; p < 0.05), indicating greater SOM diversity. Pergamino soils showed smaller differences, reflecting site-specific effects. Enzyme activities also responded to land use. In Anguil, xylosidase, β-1,4-N-acetylglucosaminidase, and phosphatase peaked under PI (40, 127, and 443 nmol g⁻¹ h⁻¹). In Pergamino, xylosidase and β-1,4-N-acetylglucosaminidase were higher under PA and PI, indicating enhanced microbial functionality under low disturbance. Fungal composition varied with land use and location: Mortierellomycetes dominated in Pergamino, while Leotiomycetes and Agaricomycetes were more abundant in PI and PA, and Dothideomycetes increased in MO and RO. Despite compositional shifts, fungal diversity changed little. Integrating chemical, biochemical, and molecular indicators revealed how land-use intensification modifies SOM and microbial processes in Pampas soils.

1. Introduction

The intensification of agriculture in the Pampas has led to significant soil degradation, including the loss of soil organic matter (SOM) and essential macronutrients in both semi-arid and humid ecoregions [1]. The conversion of native vegetation into agricultural lands has significantly reduced SOM content, while agricultural practices such as monoculture have exacerbated this decline, leading to long-term soil degradation [2]. Since the 1960s, agricultural expansion has replaced mixed farming systems with exclusively agricultural landscapes, driven by technological innovations like herbicide-resistant transgenic soybeans. This expansion has resulted in deforestation and the conversion of grasslands, negatively impacting soil structure and ecosystem stability [3]. As a consequence, the intensification and expansion of agriculture in this ecosystem have simplified landscapes, increasing dependence on external inputs and reducing biodiversity. The sustainability of these agricultural systems and their impact on microbial biodiversity remain uncertain due to the risks and challenges associated with the overuse of natural resources [3,4].

Molecular characterization of SOM is essential to understanding its dynamics and the effects of management practices on carbon and nutrient fluxes. Spectroscopic techniques, particularly Fourier transform infrared (FTIR) spectroscopy, have become key tools for identifying organic functional groups and assessing their abundance [5,6]. Thus, FTIR analyses identify organic functional groups and allow comparison of their abundances based on the absorbance of these groups in soil samples. FTIR characterizes aromatic, hydroxyl, carboxyl, aliphatic, phenolic, and polysaccharide groups in bulk SOM. Furthermore, this technique offers a cost-effective approach to characterizing soil organic carbon fractions, providing reliable and practical insights for SOM chemical analysis [7]. However, although FTIR provides valuable information about SOM composition, the functional and ecological implications of these chemical shifts remain poorly understood when not linked to microbial processes such as enzyme activity and fungal functioning.

Microorganisms play a fundamental role in nutrient cycling and energy flow by converting SOM into plant-usable forms [8]. They regulate energy flow through the decomposition of organic material and contribute to maintaining soil structure. Their activity is essential for soil fertility and productivity, providing crucial ecosystem services such as nutrient recycling, pollutant degradation, and pathogen control. Soil microbial parameters, including community structure, enzyme activity, and biodiversity, serve as bioindicators of soil health and are key to sustainable management [9]. Microbial communities are highly sensitive to land-use changes, which can alter their composition and functionality, thereby impacting soil processes and fertility. Through decomposition, microorganisms recycle essential nutrients, playing a crucial role in the stabilization of organic matter, which are vital for fertility and resilience [10]. Despite this, the mechanistic links between SOM composition, enzymatic functioning, and the structure of microbial—particularly fungal—communities remain unclear. Understanding these interactions is critical for explaining how biochemical transformations of SOM translate into broader soil ecosystem functions.

In particular, fungi play a crucial role as decomposers, recycling organic and mineral components in the soil, including cellulose, lignin, carbon, and nitrogen [11]. Moreover, fungal hyphae contribute to soil aggregation and the stabilization of their necromass, as they can be viewed as a ‘sticky-string bag’ that promotes the entanglement and enmeshment of soil particles [12]. These processes are essential for SOM accumulation and soil structure formation, contributing to overall soil health and stability. Agricultural practices can significantly impact fungal communities and soil quality, depending on the edaphoclimatic conditions [13]. Some intensive agricultural management practices such as tillage and fertilization can modify the abundance, diversity, and composition of soil fungal communities and enzyme activities, ultimately affecting plant nutrient levels and key ecosystem functions. In fact, enzymatic activities in cultivated soils tend to decrease compared to uncultivated soils, and this decrease has been positively correlated with SOM and fungal biomass [14]. Thus, soil fungi play a major role in promoting enzymatic activities compared to other microbial groups even under changing conditions [14,15]. While some studies have analyzed the effect of different agricultural practices on bacterial communities [4,16], very few have investigated the relationship between the chemical composition of organic matter and soil fungi. Understanding how soil fungi respond to land-use changes is essential for unraveling soil processes that affect fertility and ensuring sustainable soil management and agricultural productivity [17,18]. By integrating SOM chemistry, enzyme activities, and fungal community dynamics, it becomes possible to obtain a more mechanistic understanding of how land-use intensification alters soil functionality across different environments.

The aim of this work was to evaluate the impact of land-use intensification on soil function and fungal abundance in contrasting ecoregions of the Argentine Pampas. For this purpose, we evaluated (i) the chemical composition of SOM estimated by FTIR spectroscopy, (ii) soil enzymes related to macronutrient cycling, and (iii) soil fungal abundances and fungal diversity using high-throughput sequencing. We hypothesized that land-use intensification would reduce SOM chemical diversity, enzyme activities, and fungal abundance, reflecting a decline in soil biological functionality. Moreover, we expected these effects to be more pronounced in the semi-arid ecoregion (Anguil) than in the humid one (Pergamino), due to differences in edaphoclimatic conditions. This integrated approach aims to bridge the current gap between SOM characterization and microbial ecology, providing new insights into the mechanisms that drive soil functionality under agricultural intensification.

2. Materials and Methods

2.1. Experimental Design and Soil Sampling

Medium-term experiments were conducted in the Argentine Pampas to assess the impact of land-use intensification: an undisturbed environment (pristine, PI), pasture (PA), crop rotation with cover crops (RO), and monoculture (MO). The same experimental design for land uses was applied at two locations that belong to different ecoregions: Anguil (36°36′ S, 63°58′ W, 165 m a.s.l.), in the semi-arid region of the Dry Pampas (Pampa Seca), and Pergamino (33°56′ S, 60°34′ W, 65 m a.s.l.), in the sub-humid region of the Humid Pampas (Pampa Húmeda). The soil of Anguil is classified as a Petrocalcic Paleustoll with a loam texture (9.3% clay, 41.8% silt, and 48.9% sand), while the soil of Pergamino corresponds to a Typic Argiudoll with a silt loam texture (29.8% clay, 57.4% silt, and 12.8% sand). The details of each treatment at each location is shown in

Table 1. Detail of the two contrasting locations and land uses included in the present study.

Location	Land Use	Land Management	Management History
Anguil	PI	Natural grassland dominated by Stipa tenuis, Poa ligularis, Bromus brevis, Piptochaetium napostaense, and Prosopis caldenia Burkart (Caldén woodland)	Agriculture experimental plots were established in 2009 in a production field belonging to the CREA group in La Pampa Province, Argentina. Soybean was sown under no-tillage in December at 24 plants m−2 with 0.52 m row spacing and harvested in May. Cover crops were sown at 80 seeds m−2 in late May and fertilized with 40 kg N ha−1, and terminated with glyphosate in October.
	PA	Alfalfa (Medicago sativa L.) and Festuca (Festuca arundinacea)
	RO	Soybean/corn rotation with Centeno (Secalecereale L.)
	MO	Soybean monoculture
Pergamino	PI	Natural grassland dominated by Stipa spp., Cynodon dactylon, Paspalum spp., along with various forbs like thistles (Carduus pycnocephalus and Dipsacus fullonum).	Agricultural experimental plots were established in 2011 at the Experimental Station of INTA Pergamino in Buenos Aires Province, Argentina. Soybean (Glycine max L., var. DM 5.1) was sown under no-tillage in November at 50 plants m−2 with 0.52 m row spacing, and weeds were controlled with post-emergent glyphosate. Cover crops were sown in April–May at 80 and 20 kg ha−1, respectively, fertilized with 14.7 kg P2O5 ha−1, and terminated with glyphosate in October.
	PA	Festuca roja (Festuca rubra)
	RO	Soybean/corn rotation with oats and tillage radish (Avena sativa L., and Raphanus sativus L.)
	MO	Soybean monoculture

and has also been reported in a previous study [4]. For both PI and PA treatments, three 50 m² sampling stations were randomly established as independent experimental units, and composite soil samples were collected within each station. Finally, for the MO and RO treatments, a strip design (50 × 10 m) with three replicates under no-tillage was established. In all treatments, a minimum spacing of 10 m between stations or strips was maintained to ensure independent sampling. Soil sampling was conducted in late April 2021 at each location across the four land-use systems. Three composite samples were collected for each treatment, with each sample comprising 5 to 7 soil cores extracted from the surface horizon (0–10 cm) in a zigzag pattern, a sampling depth representative of the biologically active layer where microbial and enzymatic processes are most sensitive to management. Thus, a total of 24 soil samples (4 land uses × 2 locations × 3 replicates) were sieved (<2 mm) and subsequently stored at 4 °C for chemical and biochemical analysis, or at −20 °C, for molecular analysis.

2.2. Soil Chemical Analysis

Soil electrical conductivity (EC) and pH were assessed using a potentiometric approach in a 1:2.5 soil-to-water suspension. Soil organic carbon (SOC) was quantified using the Walkley–Black wet oxidation method [19]. Since these soils are carbonate-free, the measured carbon can be attributed exclusively to organic carbon. The determination of total nitrogen (N) and was performed using the micro-Kjeldahl technique [20], while total phosphorus (TP) was extracted by acid digestion and measured using a SmartChem 200 nutrient autoanalyzer (Westco Scientific Instruments, Inc., Brookfield, WI, USA). The method for TP determination was based on USEPA 351.2, Rev. 2.0 [21]. Available phosphorus (phosphate) was extracted by the Bray and Kurtz method [22], while available nitrogen (nitrate) was determined using the phenoldisulfonic acid method [23]. Several of these chemical data have previously been published [4], and are included here to support an integrative analysis with fungal communities, FTIR spectra, and specific soil enzyme activities.

2.3. Soil Spectroscopic Analysis

Humic substances (HS) were extracted following the protocol of Marinari et al. [24]. Briefly, 3 g of air-dried and sieved (<2 mm) soil were placed in a 100 mL centrifuge tube, and 60 mL of 0.1 M NaOH were added. The suspension was mechanically agitated for 4 h at room temperature and subsequently allowed to decant at 4–5 °C for 24 h. The supernatant was then collected and centrifuged at 3000 rpm for 30 min to remove residual particles. An aliquot of 15 mL of the clear extract was freeze-dried for 24 h using a RIFICOR L-A-B4-C lyophilizer (Rificor, Buenos Aires, Argentina) to obtain HS as a dry powder.

The extraction efficiency was verified gravimetrically by determining the yield of HS relative to the initial soil mass, while purity was assessed by visual inspection of color uniformity and the absence of mineral residues, as well as by confirming the presence of characteristic FTIR bands typical of humic substances (e.g., stretching of O–H, C=O, and aromatic C=C groups).

Fourier Transform Infrared spectroscopy (FTIR) was used to characterize pulverized and lyophilized soil aliquots through spectroscopic analyses. Pellets were prepared by applying a pressure of 10,000 kg cm⁻² for 2 min to a mixture of 1 mg of humic substances (HS) and 200 mg of spectroscopic-grade KBr [25]. FTIR spectra were acquired in the 400–4000 cm⁻¹ range with a spectral resolution of 2 cm⁻¹, averaging 32 scans to minimize noise. Measurements were performed at room temperature using a Bruker IFS 28 FTIR spectrophotometer (Bruker Optics, Ettlingen, Germany).

The obtained spectra were baseline-corrected and normalized to the integrated total area before band integration using OPUS Spectroscopy Software, version 8.5 (Bruker Optics, Ettlingen, Germany). Band metrics were expressed as relative area contributions (i.e., the percentage of each band area over the total integrated spectral area) within the functional group windows considered in this study. Normalization of the area under the curve in this manner preserves the intrinsic ratio among bands and allows for comparison of the relative abundance of functional groups across samples, regardless of minor differences in extraction yield or pellet compression [25].

2.4. Soil Enzyme Analysis

Enzyme activities were determined using fluorogenic substrates based on 4-methylumbelliferone (MUB) [26,27]. To begin, 1 g of fresh soil was suspended in 50 mL of autoclaved sterile water, followed by 2 min of low-energy sonication (50 J s⁻¹) to obtain a soil suspension. A 50 μL aliquot of this suspension was dispensed into a black 96-well microplate (PureGrade™, GMBH + Co KG, Wertheim, Germany). Then, 50 μL of either MES buffer (C₆H₁₃NO₄SN a 0.5 M, pH 6.5) for MUB-based substrates or TRIZMA buffer (C₄H₁₁NO₃·HCl and C₄H₁₁NO₃, pH 7.2) for the AMC-based substrate was added to each well. Finally, 100 μL of the substrate solutions were added to the wells: 4-methylumbelliferyl acetate, 4-methylumbelliferyl-β-D-xylopyranoside, 4-methylumbelliferyl N-acetyl-β-D-glucosaminide, L-leucine-7-amido-4-methylcoumarin hydrochloride, 4-methylumbelliferyl phosphate, and 4-methylumbelliferyl sulfate potassium salt were used to assess the activities of esterase (carbon-cycling enzyme), xylosidase (carbon-cycling enzyme), β-1,4-N-acetylglucosaminidase (nitrogen-cycling enzyme), leucine aminopeptidase (nitrogen-cycling enzyme), phosphatase (phosphorus-cycling enzyme), and sulfatase (sulfur-cycling enzyme), respectively.

Immediately after substrate addition, the microplates were gently shaken, and fluorometric measurements (excitation 360 nm; emission 450 nm) were taken at 0, 30, 60, and 120 min using a fluorometric plate reader (Victor3 1420–050 Multi-label Counter, PerkinElmer, Waltham, MA, USA). Enzyme activities were expressed as nanomoles of MUB or AMC released per gram of oven-dried soil per hour (nmol g⁻¹ dry soil h⁻¹).

2.5. Fungal Community Characterization

Total DNA was extracted from soil samples using the DNeasy PowerSoil Kit (Qiagen, Hiden, Germany), following the manufacturer’s instructions. Amplification of the ITS1-1F region of the fungal rRNA ITS gene was performed using the HotStarTaq Plus Master Mix Kit and primers ITS1-1F-F and ITS1-1F-R [28]. Purified PCR products were sequenced in paired-end mode (2 × 300 bp) on the Illumina MiSeq platform at Novogene Bioinformatics Technology (Beijing, China). Processing and analysis of the fungal ITS sequences were carried out using the MicrobiomeAnalyst web platform, through the “Raw Data Processing” module, which implements the DADA2 pipeline (version 1.26.0) [29]. The workflow included: (1) initial quality assessment and visualization of quality profiles to define trimming parameters; (2) filtering and trimming based on quality criteria; (3) sequence dereplication; (4) error rate learning from dereplicated reads; (5) denoising to infer exact amplicon sequence variants (ASVs); (6) merging of paired-end reads; (7) chimera removal using the consensus method; and (8) taxonomic assignment using a naïve Bayesian classifier with the UNITE fungal database as reference [30]. High-quality sequences obtained after merging and chimera removal were used to construct the ASV abundance matrix. The compositional data of the fungal community were center log-ratio (CLR) transformed using the aldex.clr function from the ALDEx2 package (version 1.24.0) in R (R Foundation for Statistical Computing, Vienna, Austria) [31], with the arguments mc.samples = 128 and demon = “all”. Sequences were deposited in the European Nucleotide Archive database (ENA) under the accession number PRJEB96849.

2.6. Data Analysis

A two-way ANOVA was performed with location and land use as fixed factors, followed by Tukey’s post hoc test to assess multiple comparisons among treatments for chemical, biochemical, and microbiological variables using InfoStat Professional v.2017 and RStudio software v.4.1.1. ANOVA assumptions were verified, including the assessment of residual normality using the Shapiro–Wilk test. The LEfSe (Linear Discriminant Analysis Effect Size) approach, implemented via linear discriminant analysis (LDA) in RStudio, was used to identify key indicator genera across localities and land uses. Microbial diversity metrics of the soil communities were obtained using the Marker Data Profiling (MDP) modules of the MicrobiomeAnalyst platform [29,32]. Data were imported using default parameters, including low-count filter (minimum count of four with 20% prevalence), low-variance filter at 10% based on interquartile range, and data scaling with total sum scaling. The partial least squares structural equation modeling (PLS-SEM) approach was used to explore the direct and indirect relationships among land-use intensification, soil chemical properties, soil organic functional groups, soil enzyme activities, and fungal diversity. Latent variables were constructed based on groups of observed variables corresponding to different soil attributes. Path coefficients and R² values were calculated to evaluate the strength of the relationships and the amount of variance explained by each latent construct. The statistical significance and robustness of path coefficients were assessed using a non-parametric bootstrapping procedure implemented in the seminr package in R. A total of 1000 bootstrap resamples were generated to estimate standard errors, t-statistics, p-values, and 95% confidence intervals for each path coefficient. Finally, Pearson correlation coefficients and their statistical significance were calculated among quantitative variables, which corresponded to those previously used to construct the latent variables in the PLS-SEM analysis.

3. Results

3.1. Soil Chemical and Spectroscopic Analysis

In summary, total carbon (TC) and total nitrogen (TN) showed significantly lower values under monoculture (MO) and higher levels under PA and PI soils in both Anguil and Pergamino (Table S1). Electrical conductivity (EC) reached the highest values under PI, particularly in Anguil, while soil pH was lowest under PI in the same locality. Total phosphorus (TP) was also significantly high under PI in Anguil. The lowest concentrations of nitrate and phosphate were observed under PI and PA in Pergamino, respectively, whereas the highest values were found under PA and PI in Anguil. The TC/TN ratio remained stable regardless of land use or location. Significant interactions between land use and locality were observed for all measured chemical variables. In the present study, these chemical parameters were reintegrated into the analysis to evaluate their relationships with newly acquired data on FTIR spectral profiles, specific soil enzyme activities, and fungal community structure.

The infrared spectral analysis of soil samples from two locations revealed distinct patterns in the functional composition of SOM (Figure 1,

Table 2. IR band intensities of HS under different land uses across two contrasting locations in the Argentine Pampas. Different letters indicate significant differences between treatments according to Tukey’s test (p < 0.05).

Infrared Band		Anguil				Pergamino
	Funcional Group	MO	RO	PA	PI	MO	RO	PA	PI
I3400	Amide A OH/NH	0.47 ± 0.30 ab	0.74 ± 0.06 bc	0.30 ± 0.04 a	0.90 ± 0.08 c	0.33 ± 0.05 a	0.37 ± 0.07 a	0.44 ± 0.09 ab	0.62 ± 0.05 abc
I2970	Aliphatic CH	0.43 ± 0.10 bc	0.55 ± 0.04 c	0.23 ± 0.02 a	0.37 ± 0.06 abc	0.30 ± 0.03 ab	0.27 ± 0.06 ab	0.24 ± 0.03 ab	0.30 ± 0.01 ab
I2854	Aliphatic CH	0.34 ± 0.03 ab	0.49 ± 0.04 b	0.19 ± 0.01 a	0.23 ± 0.05 a	0.24 ± 0.02 a	0.18 ± 0.05 a	0.20 ± 0.04 a	0.26 ± 0.01 a
I1750	Carboxyl. C=O	0.35 ± 0.06 ab	0.35 ± 0.04 ab	0.11 ± 0.02 a	0.52 ± 0.12 b	0.12 ± 0.01 a	0.16 ± 0.04 a	0.12 ± 0.02 a	0.14 ± 0.00 a
I1646	Aromatic/Amide I	0.41 ± 0.05 abc	0.48 ± 0.02 bc	0.22 ± 0.02 a	0.56 ± 0.06 c	0.24 ± 0.02 a	0.25 ± 0.04 a	0.29 ± 0.04 ab	0.38 ± 0.03 abc
I1505	Aromatic C=C	0.66 ± 0.04 a	0.71 ± 0.03 a	0.58 ± 0.07 a	0.45 ± 0.14 a	0.63 ± 0.04 a	0.59 ± 0.03 a	0.61 ± 0.06 a	0.62 ± 0.02 a
I1450	Alkane CH2/CH3	0.99 ± 0.01 a	1.00 ± 0.00 a	0.86 ± 0.05 a	0.81 ± 0.10 a	0.89 ± 0.10 a	1.00 ± 0.00 a	0.91 ± 0.09 a	0.99 ± 0.01 a
I1411	Carboxyl. COO−	0.64 ± 0.04 a	0.67 ± 0.03 a	0.55 ± 0.06 a	0.60 ± 0.06 a	0.55 ± 0.07 a	0.62 ± 0.02 a	0.51 ± 0.08 a	0.44 ± 0.02 a
I1337	Polysac. C–O	0.38 ± 0.06 a	0.34 ± 0.06 a	0.17 ± 0.02 a	0.39 ± 0.08 a	0.16 ± 0.02 a	0.21 ± 0.03 a	0.19 ± 0.03 a	0.20 ± 0.02 a
I1226	Polysac. C–O–C	0.33 ± 0.09 b	0.26 ± 0.05 ab	0.08 ± 0.02 a	0.27 ± 0.07 ab	0.05 ± 0.01 a	0.09 ± 0.04 a	0.05 ± 0.01 a	0.05 ± 0.00 a
I1023	Polysac. C–O	0.35 ± 0.09 b	0.31 ± 0.04 b	0.10 ± 0.02 a	0.35 ± 0.02 b	0.08 ± 0.01 a	0.14 ± 0.03 a	0.10 ± 0.01 a	0.10 ± 0.01 a

and Table S2). The absorption band near 3400 cm⁻¹, associated with hydroxyl and amine groups (I3400), showed higher intensities under PI and RO soils in Anguil. In contrast, MO and PA exhibited lower values. Bands linked to aliphatic structures, specifically methyl and methylene C–H stretching (I2970 and I2854), were more intense under RO, particularly in Anguil. Furthermore, the carbonyl band (I1750), typically attributed to carboxylic acids, ketones, and esters, showed markedly higher intensity under PI in Anguil. In contrast, this band remained consistently low across treatments in Pergamino. The band at 1646 cm⁻¹ (I1646), associated with conjugated C=O and aromatic C=C structures, followed a similar trend, with higher values under PI and RO. Bands assigned to aromatic ring vibrations (I1505, I1450, and I1411) did not vary significantly among treatments or locations. Overall, in the lower spectral region, bands such as I1337, I1226, and I1023 (associated with C–O and C–O–C vibrations in alcohols, ethers, phenolics, and polysaccharides) showed the highest intensities, particularly under PI and RO.

3.2. Soil Enzyme Activities

Overall, the highest enzyme activity levels were recorded under PA and PI, although this pattern was influenced by the location (Figure 2, Table S3). For C-related enzymes, no consistent trend was observed for esterase; however, the highest xylosidase activity was detected under PA and PI, particularly in Anguil. The N-related enzymes were strongly affected by land use in both Anguil and Pergamino. With some exceptions, the highest activities of both acetylglucosaminidase and leucine aminopeptidase were found under PA and PI. Finally, the highest phosphatase activity was recorded under PA and PI in Anguil, while the lowest sulfatase activity was observed under MO in Pergamino.

3.3. Fungal Community

Across all soil samples, a total of 664,363 high-quality fungal sequences were obtained. In Anguil, 16.0%, 15.4%, 19.3%, and 19.9% of the ASVs were unique to MO, RO, PA, and PI, respectively, while 29.4% were shared across all land-use treatments. In Pergamino, 16.5%, 13.1%, 18.4%, and 23.9% of the ASVs were exclusive to MO, RO, PA, and PI, respectively, with 27.9% shared among all treatments (Figure S1).

The relative abundance of fungal classes in soils from Anguil and Pergamino was estimated using the ITS1 region (Figure 3, Table S4). Taxonomic classification revealed that the dominant fungal classes across all samples included Sordariomycetes, Mortierellomycetes, Dothideomycetes, Eurotiomycetes, Agaricomycetes, Leotiomycetes, Rhizophydiomycetes, Pezizomycetes, Spizellomycetes, and Malasseziomycetes. Overall, Mortierellomycetes exhibited significantly higher abundance in all samples from Pergamino (Figure 4). In Anguil, Dothideomycetes showed significantly greater abundance in RO compared to the other treatments, whereas Rhizophydiomycetes reached its highest levels in PA. Spizellomycetes displayed similar patterns in both locations, with peak abundances in MO and PA. Agaricomycetes was most abundant in PA, but showed significantly lower relative abundance under MO in Pergamino and RO in Anguil. Eurotiomycetes showed a different trend depending on location, with higher values under PI and PA in Anguil and Pergamino, respectively. However, Leotiomycetes was more abundant under PI in both Anguil and Pergamino. Finally, Sordariomycetes, Malasseziomycetes, and Pezizomycetes did not exhibit significant differences in relative abundance across treatments.

LEfSe analysis (LDA threshold = 2) revealed several fungal indicator genera associated with location. In Anguil soils, these included Cosmospora, Lectera, Knufia, Lophiostoma, and Rhizophydium, whereas Fusarium, Myxocephala, Schizothecium, and Mortierella were more abundant in Pergamino (Figure S2). Similarly, LEfSe analysis by land use identified distinct indicator genera for each treatment. MO soils were characterized by exclusive enrichment of Entoloma, Spizellomyces, Pseudopithomyces, Clitopilus, and Aspergillus. RO soils showed higher abundance of Articulospora, Alternaria, Lophiostoma, Fusicolla, and Mycosphaerella. In PA, the indicator genera included Podospora, Collembolispora, Gliomastix, Gibberella, and Bipolaris. Finally, PI soils exhibited strong associations with Cylindrocarpon, Cladophialophora, Mycocentrospora, Auxarthron, and Trichospora.

To assess the effect of site and land use on fungal diversity at the species level, alpha diversity indices were estimated (Figure 5, Table S5). The Shannon index did not reveal significant differences among treatments, suggesting relatively homogeneous diversity across land uses and locations. In contrast, the Fisher index showed significant differences under PA in Anguil, surpassing those observed in RO from Pergamino.

3.4. Ecological Linkages Between Soil Chemical Properties, Enzyme Activities, and Fungal Diversity

The partial least squares structural equation models (PLS-SEM) revealed some specific pathways by which land-use intensification affected soil functioning in Anguil and Pergamino (Figure 6a). Land-use intensification in Anguil had a strong negative effect on soil chemical properties, while showing a moderate positive effect on soil organic functional groups, and a strong negative effect on fungal diversity. Soil chemical properties showed a strong positive effect on soil enzyme activities, explaining nearly all of their variance. The effect of organic functional groups on enzyme activity was negligible (β = 0.03), while fungal diversity was moderately explained by the model (R² = 0.43). Pearson correlation matrices supported the structural model findings and revealed additional patterns (Figure 6b). Thus, soil chemical properties such as pH, TC, TN, and nitrates were positively correlated with FTIR peaks such as I1505, I1450, and I1646, many of which were also positively associated with enzyme activities. In particular, xylosidase and phosphatase showed significant correlations with most of the evaluated chemical variables. Furthermore, fungal diversity (Fisher index) was positively correlated with nitrate concentrations and negatively correlated with the spectral indices I2970 and I2854.

On the other hand, land-use intensification in Pergamino negatively affected both soil chemical properties and soil organic functional groups (Figure 6a). However, it had no significant effect on fungal diversity (β = −0.28), and the model explained little of its variance (R² = 0.08). As in Anguil, soil chemical properties positively influenced enzyme activities, though with moderate explanatory power (R² = 0.65). The effect of organic functional groups on enzyme activity was negative (β = –0.41), in contrast to the weakly positive association observed in Anguil. Some chemical properties such as pH, TC, and TN were positively correlated with the infrared bands I3400 and I1646, while nitrate showed negative correlations with both I3400 and I1646 (Figure 6b). Sulfatase activity was positively associated with pH, OM, and TN, and negatively correlated with nitrate. Finally, some FTIR peaks, particularly I2970 and I2854, showed a positive correlation with fungal diversity indices (Shannon index).

Based on the bootstrapped path coefficients, the model also provides quantitative insights into how land-use practices could be managed to maintain soil functionality. For instance, in Anguil, land-use intensification had a strong negative effect on soil chemical properties (β = −0.87), which in turn strongly and positively influenced enzyme activities (β = 1.08). This suggests that maintaining soil chemical properties within the upper ~30–40% of their observed range would buffer declines in microbial-mediated nutrient cycling under intensified management. Practices such as perennial pastures or crop rotations with residue retention are therefore expected to sustain adequate enzymatic activity. Similarly, in Pergamino, although land-use intensification also reduced soil chemical properties and soil organic functional groups, maintaining these properties above intermediate levels would help preserve enzyme activities and microbial functioning despite intensive management. These observations provide actionable guidance for soil conservation, linking structural pathways to practical management strategies.

4. Discussion

4.1. Soil Properties and Organic Matter Composition Across Land Uses and Location

As expected, soils from pasture (PA) and pristine (PI) areas in both Anguil and Pergamino exhibited the highest levels of total carbon (TC) and total nitrogen (TN), whereas intensive agricultural use significantly reduced these parameters. Similar trends have been reported for Pampas grassland soils by [33], where conversion to cropland led to comparable declines in TC and TN. However, unlike those studies, our results show that the magnitude of this decline differs between the semi-arid and sub-humid sites, likely reflecting differences in soil texture and management history. This trend was reflected in the infrared (IR) spectral bands, which were associated with more abundant and diverse functional groups in soils with higher SOM. Conversely, agricultural soils (particularly those under MO) exhibited IR patterns consistent with simpler and potentially degraded organic matter. Notably, PI soils in both locations showed high absorbance in bands such as I3400 (OH/NH) and I1646 (aromatic-amide). The I3400 band may be related to total carbon content due to the presence of OH groups in organic compounds, such as humic and fulvic acids. Similarly, the I1646 band may also reflect total carbon levels, since they are associated with proteins and other nitrogenous compounds [34]. The dominance of these oxygen- and nitrogen-containing functional groups suggests active biogeochemical cycling, as they are typically produced during microbial decomposition and humification processes. Hence, stronger absorbance in these regions indicates that soils under PI maintain dynamic SOM turnover, where the continuous input of plant residues and microbial metabolites promotes both carbon stabilization and nutrient recycling. This mechanism reflects a self-sustaining system in which high-quality organic inputs and microbial activity reinforce each other, maintaining soil fertility and resilience. On the other hand, the presence of tree strata patches within the natural grassland under PI in Anguil may influence organic matter accumulation and the production of organic acids. Tree roots and decomposing leaf litter can increase the concentration of carboxylic acids and other organic compounds in the soil, contributing to acidity and an increase in the I1730–1775 band. Additionally, microbial activity in organic matter-rich soils can further promote the production of organic acids, enhancing soil acidity through a priming effect [35]. To our knowledge, this is the first study to establish relationships between soil organic functional groups and soil chemical properties in the Pampas. Nevertheless, previous studies in Pampas ecosystems have explored SOM quality through other approaches such as chemical fractionation [36], and our FTIR-based results complement these findings by providing molecular-level evidence of land-use effects.

An increase in aliphatic components in soils, as indicated by stronger absorbance in the I2970 and I2854 bands, may be linked to more intensive agricultural use (such as MO and RO). This suggests an accumulation of simpler, less decomposed organic compounds, such as lipids, waxes, and cutin-derived residues, which are more resistant to microbial degradation [37]. In intensively managed soils, frequent disturbance (e.g., tillage), coupled with reduced plant diversity and decreased inputs of complex organic matter (e.g., lignin-rich material) may limit the formation of more humified compounds. Consequently, organic matter composition shifts toward more labile and aliphatic structures [38]. From a biogeochemical perspective, this shift indicates a decoupling between carbon inputs and microbial decomposition efficiency, leading to the accumulation of energy-poor, hydrophobic materials that contribute little to nutrient retention or soil aggregation. Mechanistically, this reflects a loss of microbial processing capacity and a weakening of the feedbacks that sustain carbon sequestration and soil structure, ultimately compromising soil ecosystem functions. Such conditions reduce the potential for long-term carbon sequestration and weaken SOM–mineral associations that stabilize organic carbon in the soil matrix. Moreover, the degradation of agrochemicals by soil microorganisms depends on the chemical structure of the pesticides, influencing both their degradation rate and the persistence of aliphatic compounds in the soil [39]. These alterations can further modify microbial community composition, favoring taxa adapted to low-quality carbon sources and altering nutrient cycling dynamics.

Although the nitrate trend was inconsistent across land use and location, the markedly elevated phosphate concentrations observed under PI in Anguil may be associated with the greater intensity of FTIR bands corresponding to oxygenated functional groups in soil organic matter, particularly C–O–C and C–O vibrations (bands I1226, I1023, and I1337). These functional groups, commonly found in polysaccharides, alcohols, and ethers [40], are known to enhance phosphate retention through hydrogen bonding or complexation with metal ions such as Ca²⁺ or Fe³⁺. This aligns with previous findings indicating that C–O and C–O–C functional groups (particularly in the 1000–1300 cm⁻¹ range) aid the retention of cations such as Ca²⁺ and may therefore stabilize phosphate in soils [41]. In semi-arid Anguil, where soils are inherently less fertile, such stabilization mechanisms play a critical ecological role in maintaining phosphorus availability. Conversely, in Pergamino (characterized by a more humid climate and naturally fertile soils) the reduced intensity of these FTIR bands suggests a simpler or more decomposed organic matrix, which may contribute to the lower phosphate levels observed, particularly under PA. These contrasting patterns highlight the importance of both soil organic matter quality and local eco-edaphic context in modulating phosphorus dynamics across land-use systems. Such spatial variation also implies differential vulnerability to future climate extremes, such as prolonged droughts in semi-arid Anguil, which could further challenge soil nutrient availability and microbial-mediated processes. Ecologically, this suggests that land-use intensification interacts with climate to shape the functional stability of soil systems, with semi-arid soils being more sensitive to nutrient depletion and loss of microbial resilience. Finally, the absence of significant differences in bands I1505, I1450, I1411, and I1337 suggests that the associated functional groups (mostly recalcitrant or widely distributed in soil organic matter) are relatively stable across land uses and locations.

4.2. Soil Enzyme Activity and Its Relationship with Organic Matter Quality

Our study revealed clear variation in soil enzyme activities across land uses and locations, with both carbon- and nitrogen-related enzymes showing similar trends. Except for esterase in Anguil, enzyme activities were generally higher under PA and PI, reflecting less disturbed, more natural systems that support enhanced microbial functionality. This pattern was particularly marked in the semi-arid site of Anguil, where carbon-related enzymes such as xylosidase exhibited peak activity. Thus, xylosidase activity in Anguil correlated positively with most soil chemical properties, suggesting that this enzyme may play a key role in organic matter decomposition processes under semi-arid conditions. Because xylosidase hydrolyzes hemicelluloses from plant residues, its higher activity under PA and PI likely reflects active microbial degradation of fresh litter inputs, mainly driven by fungi and actinobacteria involved in carbon turnover. Moreover, nitrogen-related enzymes, including acetylglucosaminidase and leucine aminopeptidase, showed elevated activities under PA and PI in both localities. Similar findings have been reported in previous studies carried out by our group and by other authors in comparable environments, confirming the positive impact of less intensive land use on soil biochemical functioning [4,42]. These results suggest that perennial vegetation cover and minimal soil disturbance in these land uses favor organic matter decomposition and nitrogen mineralization pathways, especially under more severe climatic conditions. The activity of these N-related enzymes indicates efficient microbial recycling of organic N substrates, such as chitin and peptides, linking enzyme activity with nutrient mineralization and microbial turnover. This effect can be explained by the greater organic matter content and the higher total nitrogen (TN) and total carbon (TC) levels observed under PI and PA, which likely provide abundant substrates that stimulate microbial activity and enzyme production [43]. Consequently, the increased activity of both carbon- and nitrogen-cycling enzymes points to improved soil fertility and nutrient availability in these systems.

Phosphatase activity mirrored these trends in Anguil, with significantly higher activities recorded in PA and PI, underscoring the role of sustainable land management in preserving phosphorus bioavailability in nutrient-limited contexts. Thus, similar to xylosidase, the enzyme phosphatase in Anguil also significantly correlated with soil chemical properties suggesting that nutrient availability and organic matter content strongly influence the enzymatic processes involved in phosphorus cycling under semi-arid conditions [44]. This integrative view suggests that management practices enhancing organic matter inputs and maintaining vegetation cover promote multiple nutrient cycles simultaneously, reinforcing the multifunctionality of less disturbed soils. This is consistent with findings from the southern Pampas [45], although the relative enzyme responses in our semi-arid site were stronger—likely due to differences in climatic constraints and agricultural management practices. Interestingly, the response of sulfatase activity to land use was strongly dependent on location. In Anguil, sulfatase activity showed no changes, whereas in Pergamino, the activity of this enzyme was markedly decreased, with very low values under MO. This trend may be associated with the fact that higher sulfatase activity in Pergamino can be maintained in soils with greater organic matter content, except under highly intensive land uses. Previous studies have described a close relationship between certain organic matter fractions, such as glomalin, and the content of organic sulfur and sulfatase [46]. Because sulfatase acts on ester-sulfate bonds in SOM, its decline under intensive use likely reflects substrate depletion and reduced microbial synthesis of sulfur-related enzymes.

Although the enzymes analyzed in this study are mainly hydrolytic and reflect the turnover of labile organic matter fractions, soil microbial communities also produce oxidative enzymes that play a crucial role in the degradation of more recalcitrant compounds, including lignin derivatives and xenobiotics. Recent studies have shown that bacterial cytochrome P450 enzymes and novel hydrolases are involved in the biodegradation of persistent fluorinated and aromatic compounds in soils, highlighting the metabolic versatility of microbial consortia in degrading complex carbon structures [47]. Although such enzymes were not measured here, their presence likely complements the hydrolytic processes observed, collectively supporting SOM turnover under different land-use intensities.

The observed variation in soil enzyme activities across land uses and locations also has implications under projected climate change scenarios. In the semi-arid site of Anguil, where enzyme activities such as xylosidase and phosphatase are closely linked to organic matter and nutrient availability, expected intensification of drought events could reduce soil moisture and constrain microbial activity, potentially impairing nutrient cycling. In contrast, Pergamino soils are more fertile and humid may buffer some functional declines, although intensive agricultural systems like monocultures remain vulnerable. These findings highlight the interactive effects of land use, soil properties, and climatic stressors on soil biochemical functioning, suggesting that less intensive management and maintenance of vegetation cover could enhance the resilience of microbial-mediated processes under increasingly extreme environmental conditions.

4.3. Fungal Community Structure and Diversity in Response to Land Use and Location

Our study also indicated that land use and location altered the relative abundance patterns of fungal classes. The predominant fungal phyla in the soil samples were Ascomycota and Basidiomycota, with a notable representation of classes such as Eurotiomycetes, Sordariomycetes, Dothideomycetes, Agaricomycetes, and Mortierellomycetes. Although this taxonomic distribution is consistent with previous reports on soil fungal communities [48,49], the present study is the first to document the effect of land use on fungal communities in the Pampean region.

The identified classes encompass functionally diverse groups that play a pivotal role in soil health, fertility, and overall ecosystem functioning through multiple life strategies and interactions with other members of the soil microbiome. Notably, the class Mortierellomycetes exhibited significantly higher abundance in all samples from the sub-humid Pergamino site. This pattern may be associated with differences in climatic conditions between locations, particularly soil moisture content. Several studies have highlighted moisture as a key driver of fungal community composition, as it directly influences fungal growth and activity [50]. Specifically, higher water content has been shown to favor the proliferation of fungi belonging to Mortierellomycota, as observed in tea plantations where this fungal class was more abundant in wetter soils [50].

Land use was also associated with an increase in the abundance of various fungal taxa. For instance, the class Leotiomycetes, belonging to the phylum Ascomycota, exhibited significantly higher abundance under PI in both Anguil and Pergamino, suggesting a preference for less disturbed soils with higher organic matter content. This trend is consistent with previous studies indicating that several taxa within this class are efficient saprotrophs or facultative symbionts that thrive in stable soil conditions with high availability of complex organic residues [51,52]. Furthermore, Agaricomycetes, belonging to the phylum Basidiomycota, showed the highest abundance under PA in both locations. This class includes numerous fruiting body-forming fungi and decomposers of lignocellulosic organic matter, commonly associated with soils rich in plant debris and more stable conditions [53]. The observed patterns are consistent with studies highlighting the sensitivity of Agaricomycetes to land-use changes. Some authors have reported that deforestation reduces the relative abundance of Basidiomycota by more than half, particularly Agaricomycetes such as Lactarius and Inocybe [54]. Finally, the abundance of Dothideomycetes was higher under MO from Pergamino and RO from Anguil, suggesting a greater presence of this fungal class in soils under intensive agricultural use. This fungal group includes numerous saprophytic and phytopathogenic species that colonize plant residues; therefore, their presence may be related to the continuous and recent incorporation of different types of plant residues, including grasses and legumes [55]. In this regard, previous studies have indicated that agricultural practices can promote the abundance of potentially pathogenic fungi, such as those belonging to Dothideomycetes, due to soil disturbance, reduced microbial diversity, and the accumulation of plant residues [56].

The LEfSe analysis (LDA > 2) identified fungal indicator genera whose differential abundance was associated with the sampling location. The genera identified in Anguil include several taxa linked to more extreme environmental conditions or nutrient-poor soils. For example, Knufia is a melanized fungus known for its resistance to environmental stress, including high UV radiation and desiccation, traits consistent with semi-arid environments [57]. In Pergamino, the fungal genera Fusarium, Myxocephala, Schizothecium, Cylindrocarpon, and Mortierella were predominant indicators. The abundance of Fusarium and Cylindrocarpon appears to be linked to the sub-humid conditions of the region, where soil moisture facilitates their persistence, spore dispersal, and infection processes in host plants [58]. In our study, land use emerged as a major driver of fungal community structure, with each management system harboring distinct indicator taxa. The exclusive occurrence of Spizellomyces in soybean monoculture may be linked to soil disturbance associated with intensive management, as chytrid populations, including Spizellomyces, can increase under such conditions [59]. Meanwhile, the presence of Aspergillus (a genus capable of degrading cellulose and lignin under nutrient stress) likely reflects the continuous input of soybean residues [60]. Crop rotation favored Alternaria and Lophiostoma, which may indicate pathogen accumulation from frequent legume phases [61] and the coexistence of endophytes and saprotrophs adapted to stable, less stressful root environments [62,63]. Pasture systems were characterized by Podospora, a lignocellulose-degrading saprotroph, and Gibberella, an endophyte of grasses that can also contribute to nutrient mobilization in low-disturbance soils [64]. Finally, undisturbed sites showed greater representation of Trechispora, a specialist in degrading lignin-rich plant material typical of mature systems [65].

Despite the variation in the abundance of fungal taxa associated with land-use change, diversity indices showed only minor differences. This lack of significant variation in diversity metrics, even when taxonomic composition shifts, may reflect the limitations of conventional indices in capturing the full complexity of soil microbial communities, including taxonomic, functional, and phylogenetic dimensions. In this context, the balance between diversity and functional composition becomes particularly relevant. Previous studies have shown that in soils with low biodiversity, the addition of species can enhance ecosystem functions, whereas in highly diverse systems, community composition often has a stronger influence than species richness [66]. Moderate disturbances, such as those occurring in cultivated soils, can promote diversity, while undisturbed soils tend to harbor specialized, efficient microbial communities optimized for enzymatic activity despite lower diversity [67]. Therefore, soil functionality depends on both overall diversity and the presence of key functional taxa. Excessive diversity combined with limited dispersal and stochastic effects may reduce enzymatic activity and related soil processes, highlighting the complex relationships between diversity, functional redundancy, and ecosystem functioning. In the context of climate change, where shifts in precipitation patterns and an increased frequency of extreme events are expected, functional redundancy may buffer soil processes against environmental fluctuations, ensuring the maintenance of critical microbial-mediated functions. Maintaining an appropriate balance between diversity, functional composition, and disturbance intensity is thus crucial for sustaining soil health and resilience. From a management perspective, practices that preserve organic matter inputs and minimize disturbance are likely to maintain functionally diverse fungal communities and associated enzyme activities, enhancing nutrient cycling efficiency and soil ecosystem services.

The observed patterns in fungal community structure also have implications under climate change. In the semi-arid site of Anguil, where taxa such as Knufia are adapted to extreme conditions, intensification of drought events could constrain the growth and activity of less stress-tolerant fungi, potentially affecting decomposition and nutrient cycling. In Pergamino, sub-humid soils favor moisture-dependent taxa like Mortierellomycetes, Fusarium, and Cylindrocarpon, which may be sensitive to increasing frequency of dry periods. Despite the minor changes in alpha-diversity, functional redundancy within fungal communities could buffer some ecosystem processes, but intensive land uses like monocultures or crop rotations might be particularly vulnerable. These results highlight the interactive effects of land use, soil microbial composition, and climatic stressors, suggesting that preserving functionally diverse and resilient communities is key to maintaining soil health under projected climate extremes.

5. Conclusions

Our study provides novel insights into the ecological consequences of land-use intensification in two contrasting ecoregions of the Argentine Pampas. In agreement with the first hypothesis, changes in SOM composition (particularly several organic functional groups) were strongly influenced by edaphoclimatic conditions and land use, shaping fungal community structure. The second hypothesis was partially supported: although no clear differences were observed in fungal diversity indices, enzyme activities and fungal abundance declined under intensive agricultural practices, indicating reduced microbial functionality and nutrient cycling. These results emphasize that microbial communities may retain apparent taxonomic stability while experiencing functional impairments. While microbial alpha-diversity is often linked with improved soil health, our findings indicate that high microbial diversity does not necessarily prevent functional decline under intensive land use. Instead, community composition and functional redundancy appear to play a key role, buffering soil processes against environmental fluctuations. Overall, our findings highlight the value of combining chemical, biochemical, and molecular approaches to assess soil health, and stress the urgent need for sustainable land management strategies that safeguard microbial processes, soil fertility, and long-term ecosystem resilience. Future research will focus on identifying key microbial species and metabolisms associated with different land uses. Understanding these soil microbial dynamics will be crucial for advancing sustainable agricultural and soil management practices.