Livestock management and compost addition shape soil microbial communities and enzymatic activities in Mediterranean agroecosystems

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Yet how these factors interact to shape soil microbial diversity, composition, and functioning remains unclear. We assessed bacterial, fungal, and arbuscular mycorrhizal (AMF) communities, together with soil enzymatic activities, under three livestock regimes (exclusion, equine, ovine) before and after compost addition in a Mediterranean olive orchard. Bacterial diversity showed no significant changes across treatments, whereas fungal and AMF diversity responded more strongly. Fungal richness differed among livestock regimes, with lowest values in exclusion plots, and both fungi and AMF declined following compost addition. These trends contrasted with the stability of bacterial richness, indicating taxon-specific sensitivity rather than uniform effects of grazing or compost. Livestock regime was the main driver of microbial composition (R² = 0.27–0.30), while compost induced significant but secondary shifts (R² ≈ 0.16–0.18). Interactive effects occurred in all microbial groups, and distinct bacterial, fungal, and AMF phylotypes characterized pre- and post-compost conditions. Compost promoted copiotrophic bacterial taxa and decomposer fungal classes. Enzymatic responses were divergent: urease decreased by 64%, glucosaminidase increased by 63%, and phosphatase declined two- to six-fold after compost addition. Grazing reduced β-glucosidase activity by 40–68%, and compost–livestock interactions shaped dehydrogenase and aminopeptidase patterns. Overall, organic inputs and herbivore identity jointly influence soil microbial assembly and nutrient cycling. These findings underscore the need to consider grazing context when evaluating compost as a strategy to enhance soil health in Mediterranean agroecosystems. Grazing management organic amendment fungal and AMF diversity soil enzymes soil functioning Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Soil microorganisms play a central role in the biogeochemical processes that sustain soil fertility, nutrient cycling and ecosystem functioning in sustainable agricultural systems. Their contribution is particularly critical in organic and regenerative farming, where biological processes substitute synthetic inputs and soil health depends largely on microbially driven carbon (C), nitrogen (N), and phosphorus (P) dynamics [ 1 ]. Among the main practices influencing soil microbial communities, the application of organic amendments, such as compost, and the management of livestock grazing stand out as key regulators of resource availability, soil structure, and microsite heterogeneity [ 2 , 3 ]. Compost, especially when produced from recycled organic residues, provides a sustained input of organic C and nutrients that nourish soil microorganisms and stimulate key enzymatic activities. These inputs enhance microbial biomass and the activity of enzymes such as β-glucosidase, urease, and phosphatase, which regulate the mineralization of C, N, and P [ 4 , 5 ]. The composition and maturity of compost, its C:N ratio, stabilization degree, and biochemical profile, strongly influence microbial diversity and functional capacity. For instance, García-Orenes et al. [ 6 ] found that compost derived from agricultural residues increased the abundance of Actinobacteria and Pseudomonadota , while Bastida et al. [ 7 ] reported that compost application enhanced oxidative enzyme activities involved in the transformation of complex organic matter. Long-term applications have been shown to improve functional redundancy and resilience within soil microbial communities, maintaining efficient nutrient cycling and improving soil structure and carbon retention [ 8 ]. Through these mechanisms, compost not only enhances short-term nutrient availability but also promotes sustained improvements in biological soil functioning, fertility, and ecosystem stability [ 9 , 10 ]. However, excessive or poorly managed compost applications can produce counterproductive effects. Over-application may lead to nutrient imbalances, especially P accumulation,, increased soil salinity, or elevated dissolved organic carbon that stimulates transient microbial respiration but accelerates carbon loss [ 11 , 12 ]. Immature or unstable composts can temporarily immobilize N, release phytotoxic compounds, or disturb the balance of soil microbial communities [ 3 ]. Thus, the quality, maturity, and application rate of compost are critical factors in maximizing its benefits while minimizing adverse impacts on microbial activity and soil health. Livestock grazing represents another powerful driver of soil microbial structure and functioning. Through trampling, manure deposition and shifts in vegetation composition, grazing alters soil physical and chemical properties, plant–microbe interactions and nutrient redistribution [ 13 , 14 ]. These processes generate spatial and temporal heterogeneity in the soil environment, shaping microbial community structure, functional diversity, and enzymatic activity. When grazing intensity and livestock type are carefully managed, moderate grazing can stimulate microbial activity and promote nutrient turnover, enhancing processes such as carbon mineralization and nitrogen cycling [ 15 , 16 ]. Moreover, differences among livestock species, due to contrasting foraging behaviour, manure characteristics, and grazing patterns, can exert species-specific effects on soil biota and their ecological functions [ 14 ]. Conversely, long-term continuous grazing under high stocking densities often degrades soil health. Persistent trampling and nutrient imbalance can reduce soil organic carbon and nitrogen reserves, limit microbial biomass, and disrupt community composition, ultimately compromising soil fertility and ecosystem multifunctionality [ 17 , 13 ]. Soil compaction further restricts gas diffusion and water infiltration, while limited organic matter inputs constrain microbial metabolism and enzymatic expression, leading to reduced biogeochemical efficiency [ 15 ]. To mitigate these impacts, the strategic implementation of resting periods or grazing exclusion zones, areas where livestock are temporarily or permanently removed, has proven effective in supporting the recovery of soil structure and biological activity [ 15 , 18 ]. However, as highlighted by Shu et al. [ 19 ] in their global meta-analysis on grazing exclusion and soil microbiomes, our understanding of how the duration, frequency, and timing of resting periods affect microbial succession, enzymatic functioning, and long-term soil fertility remains limited. Their study demonstrates that while grazing exclusion generally promotes microbial recovery, the magnitude and direction of these effects vary considerably with exclusion duration, grassland type, and climatic conditions. Shu et al. [ 19 ] emphasized that the ecological mechanisms underpinning these variations are still poorly resolved, particularly regarding how intermittent or rotational exclusion regimes influence microbial resilience and nutrient-cycling efficiency. Consequently, further long-term, mechanistic research is urgently needed to clarify the temporal dynamics of microbial responses to different grazing-rest strategies and to optimize their role in restoring soil functionality and ecosystem sustainability. As a result, there is an urgent need for long-term, mechanistic studies to clarify the temporal dynamics of microbial responses to different grazing–rest strategies and to optimize their role in restoring soil function and ecosystem sustainability. Building on this knowledge gap, an additional layer of complexity emerges when considering how grazing-rest strategies interact with other management practices. Despite growing evidence on the independent effects of compost application and grazing, their combined influence on soil microbial communities and enzymatic functioning remains largely unresolved. In Mediterranean agroecosystems, where organic amendments and mixed livestock systems are increasingly common, clarifying these interactions is essential for designing effective soil regeneration strategies that integrate both grazing management and organic inputs. In this study, we aimed to examine how livestock management and compost addition shape soil microbial diversity, community structure and functional activity in an olive organic cultivation area. Specifically, we pursued the following objectives: 1) To assess the effects of different livestock management regimes (ovine grazing, equine grazing, and grazing exclusion) on bacterial, fungal and arbuscular mycorrhizal diversity and community composition 2) To evaluate the impact of compost addition on microbial diversity and composition, and to determine whether its influence differs across livestock management types. 3) To quantify changes in soil enzymatic activities related to C, N and P cycling in response to compost addition and livestock presence. 4) To identify specific microbial phylotypes associated with compost addition within each livestock regime, thereby determining whether grazing history modulates microbial indicators of organic amendment inputs. We hypothesize that the response of soil microbial communities and enzymatic activities to compost addition is strongly modulated by livestock management, with grazing regime determining the extent to which compost can enhance microbial diversity, functional structure and nutrient-cycling processes. Specifically, we anticipate that soils under ovine grazing will show more pronounced shifts in microbial structure and enzymatic activities in response to compost addition compared to equine grazing or grazing exclusion, reflecting the cumulative influence of more intensive grazing on soil biotic and abiotic conditions. 2. Materials and Methods 2.1 Experiment design The Cortijo el Puerto farm, located in Lora del Río (Seville, Spain), was chosen as the site for soil sampling used in a container trial. The property covers an area of 220 hectares, mainly devoted to olive ( Olea europaea ) cultivation in hedgerow systems. The dominant varieties are Arbosana and Arbequina , arranged in a 5 m × 1.5 m planting layout, resulting in a density of about 1,200 trees per hectare. Irrigation is supplied through drip lines placed beneath each tree row, with water distribution managed under the authorization of the Guadalquivir Hydrographic Confederation. The farm operates under organic farming standards, emphasizing sustainable and eco-friendly practices. A no-till approach is implemented, and livestock, specifically donkeys and sheep, assist in controlling ground vegetation. The area experiences a Mediterranean climate, characterized by mild winters and hot, dry summers. Average minimum and maximum temperatures range from 2.6°C in January to 33.8°C in August, and the mean annual precipitation is approximately 475 mm. The soil at the site is classified as an Entisol, Typic Xerofluvent (Soil Survey Staff, 2006) with a sandy clay loam texture (28% clay, 27% silt, and 44% sand, according to the USDA classification). The soil presents a pH of 8.0, an organic carbon content of around 4%, and nutrient levels of 4 g kg⁻¹ nitrogen, 45 mg kg⁻¹ P, and 250 mg kg⁻¹ potassium (K). The experimental design comprised three delimited and fenced areas with different livestock management: (1) livestock exclusion, (2) equine, and (3) ovine livestock (Fig. 1 ). The livestock exclusion area, covering approximately 35 hectares, has been maintained free of grazing for six months. The livestock-managed areas have been subject to rotational grazing since 2016, following the sowing of native legumes and grasses in 2015. The ovine area encompasses approximately 75 ha and is grazed by around 150 sheep (2 sheep/ha), specifically of the Churra, Merina and Lebrijana breeds. The equine area covers about 10 ha and is grazed by 15 adult Andalusian donkeys. 2.2 Soil sampling and compost characteristics In June 2023, initial soil samples ( n = 4) were taken from the surface layer (0–15 cm) at randomly selected points within three experimental plots, approximately 25 cm from the tree trunks and irrigation drippers, using an auger for subsequent DNA and enzyme analyses. Additionally, for the compost-application assay, about 3 kg of soil per sampling area were obtained by combining portions collected with a hoe from six different locations within each livestock area. The soil was homogenized, and coarse fragments were manually removed. These composite samples were transported to the laboratory and placed into containers (approximately 450 cm² each). Compost was applied at a rate of 20 t ha⁻ 1 and incorporated into the upper soil layer by manual mixing. The containers were kept outdoors to simulate natural field conditions. After six months, in November 2023, soil subsamples (n = 3) were collected from the 0–15 cm layer of each container for DNA and enzyme analyses, allowing comparison with the initial field samples. The compost was produced entirely with by-products from the organically managed farm, following circular economy principles. A 2:1:1 mix of olive mill waste (alperujo), pruning residues, and sheep manure underwent a complete composting process, including a thermophilic phase (> 55°C for over 15 days), to stabilize organic matter and ensure pathogen elimination. A detailed description of the compost used can be found in Gil-Martínez et al . [ 20 ]. 2.3 Soil enzyme activities analysis The potential activity of four different hydrolytic enzymes involved in C, N and P cycling was assayed fluorometrically with a microplate reader (FLUOstar® Omega) using 4-methylumbelliferone (MUF) or 7-amino-4-methyl coumarin (AMC) linked-substrates: β-glucosidase, N-acetyl-β-D-glucosaminidase, acid phosphatase and leucine-aminopeptidase, following the methods described in [ 21 ]. Likewise, two enzymes, dehydrogenase and urease were assayed by absorbance-based methodology. Thus, dehydrogenase activity (DHA) was determined according to Trevors [ 22 ] after soil incubation with p-iodo nitrotetrazolium chloride (INT) and measurement of the p-iodo-nitrotetrazidin formazan (INTF) absorbance at 490 nm. Urease activity was determined according to the method proposed by Kandeler and Gerber [ 23 ]. 2.4 DNA extraction Total DNA was extracted with DNeasy® PowerLyzer® PowerSoil Kit® (Qiagen Inc.) following manufacturer´s instructions. Library preparation and Illumina sequencing were carried out at the IPBLN Genomics Facility (CSIC, Granada, Spain). Soil-extracted DNAs were quantified and normalized to 5 ng/µl. Amplicon libraries targeting the bacterial 16S rRNA gene, fungal ITS1 and arbuscular mycorrhizal fungi 18S regions were generated by a two-steps PCR strategy. Gene-specific amplification was performed in triplicate with 5–15 ng of DNA in a final volume of 10 µl. Gene specific primers were: ProV3V4fw (5'-CCTACGGGNBGCASCAG-3')/ ProV3V4rev (5'-GACTACNVGGGTATCTAATCC-3') [ 24 ] for bacteria and archaea community; fITS7fw (5'-GTGARTCATCGAATCTTTG-3') [ 25 ] and ITS4rev (5'-TCCTCCGCTTATTGATATGC-3') [ 26 ] for ITS2 region and NS31fw (5'-TTGGAGGGCAAGTCTGGTGCC-3') [ 27 ] /AML2rev (5'-GAACCCAAACACTTTGGTTTCC-3') [ 28 ] for 18S region, were designed with Nextera overhang adapters. Primers were used at a final concentration of 0.2 µM and reaction was performed with 1X KAPA HiFi HotStart ReadyMix DNA polymerase (Roche Diagnostics, West Sussex, United Kingdom). Cycling conditions were 95°C/3 min, (95°C/30 s, 55°C/30 s, 72°C/30 s) x 25 cycles and then 72°C/5 min for 16S amplification; 95°C/3 min, (95°C/30 s, 57°C/30 s, 72°C/30 s) x 27 cycles and then 72°C/5 min for ITS2 amplification and 95°C/3 min, (95°C/30 s, 65°C/30 s, 72°C/30 s) x 31 cycles and then 72°C/5 min for fungal 18S amplification. Triplicates were pooled together and validated through visualization on a 1.8% (w/v) agarose gel. At this stage, amplicons were purified using NucleoMag® NGS Clean-up and Size Select Kit (Macherey-Nagel, Düren, Germany) and subjected to a final indexing PCR step using Nextera XT v2 index kit in order to introduce dual combinatorial indices and Illumina sequencing adapters. Cycling conditions were 95°C/3 min, (95°C for 30 s, 55°C for 30 s, 72°C/30 s) x 8 cycles and then 72°C/5 min. 2 additional PCR cycles were applied to 18S amplicon for a total of 10 indexing cycles. Amplicon generation was validated again through visualization on a 1.8% (w/v) agarose gel and cleaned with NucleoMag® NGS Clean-up and Size Select Kit (Macherey-Nagel). Concentration was measured on the Infinite®200 microplate reader fluorimeter (Tecan Trading AG, Switzerland,). Libraries from each analyzed region (16S, ITS2, and 18S) were combined in an equimolecular manner rendering three library pools. Final pools were run on a Bioanalyzer HS DNA chip to verify quality and size distribution, followed by Qubit® (Thermo) quantification, and then diluted and denatured as recommended by Illumina MiSeq library preparation guide. The 300x2 nt paired-end sequencing was conducted on a MiSeq sequencer. 2.6 Bioinformatics analysis of microbial communities Bioinformatic analyses were conducted to obtain high-quality bacterial, fungal, and mycorrhizal sequences. Sequence analysis was performed with dada2 v1.26.0 R package [ 29 ] which allows for the identification of amplicon sequence variants (ASVs), distinguishing true biological variation from sequencing errors and PCR artefacts [ 29 ]. After removing chimeras, artificial DNA sequences created during PCR, taxonomy was assigned using the SILVA v138.2 database [ 30 ] for 16S reads, the UNITE v10.0 database [ 31 ] for ITS reads, and the PR2 5.1.0 database [ 32 ] for 18S reads. A total of 1,531,671 good quality bacterial sequences, averaging 66,594 ± 19,603 sequences per sample, 1,248,392 fungal sequences, averaging 49,936 ± 22,819 per sample, and 1,289,644 mycorrhizal sequences, averaging 56,071 ± 24,386 per sample, were obtained. Bacterial reads accounted for 99.732 ± 0.159% abundance, so from now on we will refer to the 16S community as bacterial community. Similarly, in the 18S dataset, all the sequences presenting arbuscular mycorrhizal primary lifestyle, according to the FungalTraits v1.2 database [ 33 ], belonged to the Glomeromycotina Order, and thus were retained for further analysis representing 83.916 ± 15.985% of the total abundance. Diversity indices were calculated after rarefaction, repeating the subsampling step 100 times [ 34 ]. Each sample was subsampled to 34,900 bacterial, 21,000 fungal, and 17,700 mycorrhizal reads (Supplementary Figure S1 ) and the resulting alpha and beta diversity metrics were averaged. Richness was measured as a representative alpha diversity metric. Differences in community composition across samples (β-diversity) were evaluated with the vegan v2.7-2 R package [ 35 ] by calculating Bray-Curtis dissimilarity matrices, and performing non-metric multidimensional scaling (NMDS) to compress dimensionality into two dimensional plots. Then, the associations between enzymatic activities and microbial communities were calculated with the envfit function within the vegan package. This function fits the vectors of enzymatic activity to the microbial ordinations (NMDS), with the length of the arrow proportional to the correlation [ 35 ]. Biplots of community ordinations and enzymatic envfit vectors were generated to visualize the results. Then, the phylotypes associated with compost addition (pre- and post- compost samples) were identified using the function multipatt in the indicspecies R package using the “IndVal.g” association value [ 36 ]. In particular, this function studies the association between species patterns and combinations of groups of sites and identifies what species are most likely to be indicators of a given group of sites (here, compost addition). These phylotypes were represented as rings in a phylogenetic tree to emphasise the association between specific taxonomic groups and compost addition. The bacterial (16S sequencues) and mycorrhizal (18S sequences) phylogenetic trees were calculated by aligning sequences with the msa R package [ 37 ] and generating a maximum likelihood tree with the phangorn R package [ 38 ] using a GTR + GI model. However, due to the hypervariability in length and composition of the ITS region, it is not amenable to robust multiple alignments and phylogenetic reconstruction beyond the genus level [ 39 ]. Thus, we inferred the putative phylogenetic relationship using the Evolutionary Placement Approach (EPA) using EPA-ng [ 40 ] and GAPPA [ 41 ] to place our ITS sequences on the T-BAS Fungi v3 reference tree [ 42 ]. 2.7 Data and statistical analysis A two-way ANOVA followed by Tukey’s post-hoc test was performed to examine the effects of compost and livestock management or their interaction on alpha diversity metrics and soil enzymatic activities. 3. Results and discussion 3.1 Microbial Diversity Responses to Compost and Grazing Bacterial alpha diversity was unaffected by compost addition or livestock presence, whereas compost addition affected fungal diversity, and livestock groups affected both fungi and mycorrhizal communities (Fig. 2 A, Table S1 ). Fungal alpha diversity was lowest in the exclusion zone compared to the equine zone, a pattern that was similarly observed in mycorrhizal communities. Compost addition significantly reduced fungal alpha diversity (Table S1 ), as well as homogenized microbial communities, specially within each livestock group (Supplementary Figure S2). Fungal and mycorrhizal communities across livestock groups were further homogenized by compost addition (Supplementary Figure S2). These contrasting responses between bacteria and fungi align with previous findings showing that fungal communities are generally more sensitive than bacterial ones to changes in plant-derived resources, disturbance intensity, and organic matter quality [ 43 ]. The lack of response of bacterial alpha diversity to either compost addition or livestock presence aligns with previous studies showing that bacterial richness tends to be relatively resistant to short-term management changes, likely due to high functional redundancy and broad ecological tolerance [ 44 ]. In contrast, the observed sensitivity of fungal and mycorrhizal diversity to both compost and grazing management supports the idea that these groups are more responsive to shifts in substrate availability and soil disturbance. Xu et al. [ 16 ] demonstrated that grazing strongly modulates the structure and carbon-related functional associations of fungal communities in grasslands, emphasizing that fungi, particularly mycorrhizal taxa, respond more tightly than bacteria to herbivore-driven changes in plant inputs and soil microhabitats. The lower fungal and arbuscular mycorrhizal fungi (AMF) diversity in the exclusion zone compared with the equine plots suggests that moderate grazing may promote microhabitat heterogeneity, root turnover, and organic inputs that favour diverse fungal assemblages. This pattern is consistent with Eldridge et al . [ 2 ], who reported that grazing enhances spatial heterogeneity in soil microbial networks by altering plant community structure and nutrient redistribution. The reduction in fungal diversity (alpha and beta) following compost addition indicates that organic inputs may select for specific fungal guilds adapted to the decomposition of nutrient-rich substrates, potentially reducing overall community evenness. Similar declines in fungal diversity after organic amendments have been reported in other grassland systems, where compost inputs tend to favour copiotrophic fungal taxa [ 45 ]. Bacterial, fungal, and mycorrhizal communities presented distinct compositional patterns among livestock groups and between pre- and post-compost samples (Fig. 2 B). PERMANOVA analyses confirmed that livestock management was the main factor explaining the largest proportion of community variation across all microbial groups (R² = 0.27–0.30, p = 0.001). Nonetheless, compost application also exerted a significant influence on community structure in all cases (R² ≈ 0.16–0.18, p = 0.001). Moreover, a significant interaction between both factors was detected for bacteria (p = 0.023), fungi (p = 0.002), and mycorrhiza (p = 0.006), indicating that the compositional shifts following compost addition varied among livestock regimes. The fact that livestock explained the largest proportion of variation across all microbial groups is consistent with the growing evidence that herbivore identity and grazing intensity are major drivers of belowground microbial assembly via changes in plant community composition, nutrient cycling, and physical disturbance [ 2 , 16 ]. Compost effects, in contrast, tend to be shorter-lived and primarily linked to resource pulses that temporarily shift microbial activity and composition [ 46 ]. However, the significant interaction between compost and livestock management further suggests that the microbial response to organic inputs is context-dependent, modulated by grazing-induced differences in soil structure, resource availability, and microbial baseline composition. Likewise, Zeng et al . [ 47 ] also showed that soils with different grazing histories respond differently to nutrient additions, indicating that grazing legacies can modulate how microbial communities react to new resource inputs. Similarly, Ingram et al . [ 48 ] demonstrated that different herbivore species create distinct patterns of organic matter deposition and soil disturbance, which in turn condition subsequent microbial responses to additional organic amendments. 3.2 Comparative phylogenetic profiles of microbial communities with compost and livestock presence Although bacterial alpha diversity remained unchanged across compost treatments and livestock groups, the community underwent a substantial reorganization of specific phylotypes. Distinct distributions were observed in response to compost addition (pre- and post-) across the different livestock regimes (exclusion, equine, and ovine), indicating that shifts in community composition can occur without affecting overall richness. Chloroflexota and Actinomycetota were characteristic of the pre-compost time (dark segments) (Fig. 3 ). In contrast, Bacteroidota was more representative of the post-compost phase (light segments), consistent with taxa typically involved in the degradation of more stabilized organic substrates. These findings align with broader ecological evidence showing that Actinomycetota and Chloroflexota are often more prevalent in low-input or resource-limited soils. For example, long-term studies in grasslands without heavy nutrient additions have found high relative abundances of Actinobacteriota (~ 40%) under oligotrophic conditions [ 49 ]. Similarly, non‑cultivated soils in the Argentine Pampas exhibited elevated proportions of both Actinobacteria and Chloroflexi , in contrast to fertilized, intensively managed fields [ 50 ], a pattern consistent with an oligotrophic life-history strategy. On the contrary, Joos et al. [ 51 ] observed that soils amended annually with compost showed a marked increase in Bacteroidota (Bacteroidetes ), supporting the idea that these copiotrophic taxa are preferentially stimulated by organic resource inputs. The bacterial phylogenetic profiles observed in each livestock regime,exclusion, equine, and ovine,were distinct, indicating that each grazing zone creates a unique set of ecological conditions shaping microbial assemblages. This pattern shows that compost inputs and livestock type interact to restructure bacterial communities at the phylum level without necessarily affecting overall richness, highlighting the combined influence of resource availability and herbivore identity on soil microbial composition [ 52 ]. A similar but clearer pattern of differential occurrence was observed in the fungal communities (Fig. 3 ). Studies show that fungal communities may be more sensitive than bacteria to both grazing and compost addition because of their ecological traits and structural dependencies. For example, fungi depend on hyphal networks to explore soil microsites, making them more vulnerable to changes in porosity, moisture, or soil structure [ 53 ]. Moreover, fungi respond strongly to the degradability of organic inputs: more processed or stabilized carbon sources trigger greater shifts in fungal composition than in bacterial communities [ 54 ]. Specific fungal classes were more frequently detected in either pre- or post-compost samples, with Dothideomycetes , Eurotiomycete, Glomeromycetes , Tremellomycetes showing higher representation in pre-compost samples, while Agaricomycetes, Pezyzomicetes and Sordariomycetes appeared predominantly in post-compost samples. This shift likely reflects the response of fungi to changes in resource availability, as compost inputs promote decomposer taxa (e.g., Agaricomycetes, Sordariomycetes ), a pattern also observed in black soil systems [ 55 ] and consistent with the functional ecology described by Fernandez & Kennedy [ 56 ]. Notably, the exclusion samples exhibited the most distinctive fungal profile, characterized by a reduced presence of Sordariomycetes , one of the most abundant classes in equine and ovine plots. Sordariomycetes include many saprotrophic and plant-associated fungi that play key roles in decomposition of organic matter, nutrient cycling, and plant-fungal interactions [ 57 ]. Their lower abundance in ungrazed plots suggests that the absence of grazing may limit the availability of suitable substrates or microhabitats necessary for their establishment or persistence. Such patterns are consistent with co‑occurrence network studies showing that fungal networks are more dynamic and fragile under disturbance or altered environmental conditions, such as grazing exclusion, compared to bacterial networks [ 58 ]. Together, these observations indicate that grazing not only influences fungal abundance but also contributes to the stability and connectivity of soil fungal communities. Regarding AMF, genera such as Glomus were characteristic of the pre-compost stage across all livestock groups, whereas Funneliformis appeared to be enhanced by compost addition (Fig. 3 ). This pattern suggests that Glomus may be adapted to more oligotrophic or undisturbed soil conditions, persisting under baseline nutrient availability, while Funneliformis responds positively to increased organic inputs, likely due to its capacity to exploit enriched nutrient conditions [ 59 , 60 ]. These shifts highlight that AMF communities are sensitive to changes in resource availability and can rapidly reorganize in response to organic amendments, complementing the compositional changes observed in bacterial and fungal communities. Furthermore, the relatively compact clustering of AMF communities in ordination analyses suggests that livestock presence may have a stronger influence than compost on AMF composition, reflecting their dependence on plant hosts and root distribution patterns shaped by grazing. 3.3 Linking Microbial Composition with Functional Enzyme Responses to Organic Inputs and Livestock The addition of compost produced marked but contrasting shifts in soil enzyme activities. Urease activity declined by 64% across all livestock regimes, whereas glucosaminidase increased by 63% (Fig. 4 ), indicating that compost selectively stimulates some N-cycling pathways while suppressing others. These divergent responses align with evidence that organic inputs can reorganize microbial communities and modify nutrient-cycling functions in non-uniform ways [ 61 ]. Consistent with previous findings, our results indicate that compost enhanced specific N-linked hydrolytic activities (e.g., glucosaminidase), whereas enzymes directly related to inorganic N turnover, such as urease, exhibited more variable responses. This highlights that the microbial functional shifts induced by compost are modulated by environmental and substrate-dependent factors. Phosphatase activity declined markedly, by roughly two-, five-, and six-and-a-half-fold in exclusion, equine, and ovine plots, respectively. While compost typically increases phosphatase activity through its effects on microbial growth and organic P turnover [ 62 ], elevated P availability can downregulate enzyme synthesis via feedback inhibition, leading to reduced phosphatase expression despite organic amendments [ 63 ]. Thus, our results likely reflect context-dependent responses, where compost enriched P availability may have downregulated phosphatase activity. Livestock management exerted a distinct influence on other enzymes, most notably β-glucosidase, which reached its highest values in exclusion plots and declined by 40% and 68% in equine and ovine soils, respectively, regardless of compost addition. These patterns highlight the suppressive effect of grazing on cellulose-degrading activity, likely linked to plant biomass removal and shifts in detrital inputs. Dehydrogenase and aminopeptidase activities were shaped by the interaction between compost and livestock presence: Dehydrogenase increased strongly in equine soils (+ 77%), more moderately in exclusion plots (+ 33%), but decreased in ovine soils (− 17%); aminopeptidase showed a similar trend, increasing by 67% in equine and exclusion soils yet declining by 16% in ovine plots. These interaction effects emphasize that microbial responses to organic amendments are tightly modulated by grazing-induced differences in soil structure, nutrient inputs, and baseline microbial composition, an interpretation supported by studies showing that compost effects vary depending on initial soil microbial networks and environmental context [ 3 , 64 ]. The shits in enzymatic activity profiles were mirrored by corresponding functional associations in the microbial communities (Fig. 5 ). Prior to compost addition, bacterial assemblages in equine and ovine zones clustered with urease and phosphatase, suggesting active N- and P-cycling under grazing [ 65 , 66 ] (Fig. 5 A). In contrast, exclusion plots aligned more closely with β-glucosidase, reflecting enhanced cellulose degradation in the absence of herbivory, which resonates with evidence from Ding et al. [ 18 ] that grazing strongly influences β-glucosidase dynamics and microbial network complexity. After compost addition, the only strong association that persisted was between exclusion soils and aminopeptidase activity, suggesting a shift toward protein-degradation pathways. This result is consistent with meta-analytic evidence showing that grazing exclusion generally enhances N-acquiring enzyme activities, including proteases and aminopeptidases, due to reduced physical disturbance and increased accumulation of organic substrates that stimulate microbial protein breakdown [ 67 ]. In our case, the combination of higher organic N supplied by compost and the favourable microenvironment of ungrazed soils likely promoted peptide-degrading microbial taxa, explaining the distinct post-compost functional signature observed in exclusion plots. Fungal communities exhibited somewhat clearer functional separation than bacteria along the Deh, aminopeptidase, and glucosaminidase axes in compost-treated samples, although the differences were moderate rather than pronounced. This pattern suggests that fungi respond to changes in organic matter inputs and nutrient availability with slightly greater sensitivity than bacteria, reflecting their role in organic N and C turnover [ 68 , 69 ]. Dehydrogenase and aminopeptidase activities likely capture fungal oxidative metabolism and protein degradation, while glucosaminidase reflects chitin turnover and fungal biomass dynamics. Together, these functional trends indicate that compost stimulates fungal activity and alters community–enzyme associations more noticeably than in bacterial communities, but the effect is moderate, highlighting fungi as sensitive but not overwhelmingly dominant responders to organic amendments [ 54 ]. AMF communities, in turn, displayed comparatively compact functional structures, with significant correlations restricted to phosphatase and aminopeptidase (Fig. 5 C), suggesting that AMF traits contribute modestly but consistently to P and N-related nutrient cycling. his functional role is supported by evidence that AMF can mobilize both phosphate and organic nitrogen via hyphal uptake [ 70 ]. Importantly, the functional clustering of AMF in our study was more strongly determined by livestock presence than by compost addition: ovine soils were positioned furthest from enzyme vectors, consistent with weaker AMF involvement in nutrient mobilization under sheep grazing. This is in line with findings from Li et al. [ 71 ], who reported grazing-induced shifts in AMF community composition in wetland soils, as well as conceptual work showing that grazing intensity can reshape AMF foraging structures and network interactions [ 58 ]. Overall, our results underscore that compost stimulates nutrient-cycling pathways, but the magnitude and direction of AMF functional shifts depend critically on grazing context and herbivore identity. 4. Conclusions Our findings show that grazing management and compost addition have distinct but interrelated effects on soil microbial diversity, composition, and function in Mediterranean olive agroecosystems. Bacterial richness remained relatively stable across treatments, whereas fungal and mycorrhizal communities were highly sensitive to livestock type and organic inputs, making them valuable early indicators of soil management impacts. Herbivore identity and presence explained a large portion of microbial composition, reflecting the central role of grazing-mediated changes in plant inputs, soil microhabitats, and disturbance regimes. The addition of compost further modified community composition and consistently homogenized microbial communities. Associations between microbial composition and enzyme profiles indicate that organic fertilizers do not act uniformly but are highly dependent on the grazing context in which they are applied. Taken together, these results suggest that effective soil restoration and nutrient cycle management in olive agroecosystems require the integration of composting strategies with grazing practices. Considering the identity of herbivores and grazing intensity will be essential to predict microbial responses and maximize the functional benefits of organic fertilizers. Declarations Author Contribution E.M., P.M., L.L.dS. developed the original idea, designed the research and coordinated all field and laboratory operations. Field data were collected by E.M., P.M and L.L.dS. Data gathering was conducted by M.dC., L.L.dS. Laboratory analyses were carried out by E.M., P.M and L.L.dS. Data analysis was performed by M.dC., and L.L.dS. The manuscript was written by M.dC., and L.L.dS and with substantial contributions from all coauthors. Acknowledgement This study was supported by the projects TED2021-130964B-I00 from the Spanish Ministry of Science and Innovation (MCIN), the State Research Agency (AEI), and the European Union – NextGenerationEU/PRTR, under the projects “Biocompost and cover crops: linking soil health, circular economy and cost effectiveness in ecological Mediterranean orchards” (Bioecover). Additional support was provided through the José Castillejo Mobility Grant for Young Researchers, under the project “Changes in carbon dynamics in response to the application of organic amendments and sustainable livestock management in Mediterranean organic crops”. References Kiprotich K, Muema E, Wekesa C, Ndombi T, Muoma J, Omayio D, Tarus J (2025) Unveiling the roles, mechanisms and prospects of soil microbial communities in sustainable agriculture. 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18:18:07","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":180702,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8364916/v1/738ce871b058e62a9d346d91.html"},{"id":98897841,"identity":"8f0f2852-7973-4b02-9a1f-83175c72fa75","added_by":"auto","created_at":"2025-12-23 18:18:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":584470,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental site and key factors of the study conducted at the ‘Cortijo El Puerto’ farm in Lora del Río, Seville (Spain).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8364916/v1/16aaff52223da0bbcbb6c5ca.png"},{"id":99309839,"identity":"1c1570f1-d36d-49be-a4db-4de749076c84","added_by":"auto","created_at":"2025-12-31 16:11:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":142887,"visible":true,"origin":"","legend":"\u003cp\u003eA) Comparison of ASV/phylotype richness among the different treatments pre- or post- compost application. Letters indicate significantly different groups according to ANOVA followed by a post hoc LSD test, while asterisks denote significant differences between pre- and post-compost samples within each livestock group (t-test). B) Non-metric Multidimensional Scaling (NMDS) analysis showing the compositional differences of microbial communities among livestock groups and between pre- and post-compost samples.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8364916/v1/96526f50407b6b0c76f7a154.png"},{"id":99309451,"identity":"bf926917-5d3f-45cf-8f87-7cb58d654337","added_by":"auto","created_at":"2025-12-31 16:10:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":249059,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic trees showing the diversity of bacteria (left), fungi (middle), and mycorrhizal (right) phylotypes identified as being characteristic of compost addition. The outer and middle rings indicate whether each phylotype is associated with pre-compost (light gray) or post-compost (black) samples. The innermost rings represent taxonomic composition for bacterial (phylum level), fungal (class level), and mycorrhizal (genus level) phylotypes. Phylotypes for which taxonomic assignments did not match the tree topology were retained without manual adjustment.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8364916/v1/3e1c122ee867a6d41668cac2.png"},{"id":99309529,"identity":"976e3f70-724d-45fd-869a-14a1623d3d5c","added_by":"auto","created_at":"2025-12-31 16:10:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":176361,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of compost (C) and livestock management on soil enzymatic activities before compost addition (solid bars) or after compost (slashed bars) with three types of livestock management: excluded (salmon), equine (beige) or ovine (blue). Dehydrogenase: Desh (μg INTFg\u003csup\u003e-1\u003c/sup\u003edw h\u003csup\u003e-1\u003c/sup\u003e); β-glucosidase: β-glu, Glucosaminidase: Glu, aminopeptidase: Amin, Phosphate: Phos (μmol MUFg\u003csup\u003e-1\u003c/sup\u003edw h\u003csup\u003e-1\u003c/sup\u003e); Urease: Ure (μmoles NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003eg\u003csup\u003e-1\u003c/sup\u003e h\u003csup\u003e-1\u003c/sup\u003e). Anova results (F and \u003cem\u003ep\u003c/em\u003e-value) showing the main significant factors (i.e. livestock management, compost addition, or interaction).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8364916/v1/89af9b578ae12f61dc847e47.png"},{"id":99309901,"identity":"957367d2-5f59-4321-8ecd-3af3c925e717","added_by":"auto","created_at":"2025-12-31 16:11:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":107892,"visible":true,"origin":"","legend":"\u003cp\u003eNonmetric multidimensional scaling (NMDS) of soil A) bacterial, B) fungal, and C) mycorrhizal communities based on Bray–Curtis dissimilarities of phylotype composition. Arrows indicate the direction in which each enzymatic activity best fits the ordination space (envfit). Arrow length is proportional to the strength of the correlation between each enzymatic variable and community composition.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8364916/v1/9fc8c361db6cb6fa45dc4a13.png"},{"id":101794075,"identity":"dd198140-b9fb-4c05-923a-67b18bfaa553","added_by":"auto","created_at":"2026-02-03 16:26:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1963730,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8364916/v1/6ff67209-ef28-406b-8ec0-ff25fa797454.pdf"},{"id":99309788,"identity":"d9f25772-93d9-4179-b29b-c34b1ec066c2","added_by":"auto","created_at":"2025-12-31 16:11:09","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":211229,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-8364916/v1/3cc680beced2fbea5fc5d402.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Livestock management and compost addition shape soil microbial communities and enzymatic activities in Mediterranean agroecosystems","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSoil microorganisms play a central role in the biogeochemical processes that sustain soil fertility, nutrient cycling and ecosystem functioning in sustainable agricultural systems. Their contribution is particularly critical in organic and regenerative farming, where biological processes substitute synthetic inputs and soil health depends largely on microbially driven carbon (C), nitrogen (N), and phosphorus (P) dynamics [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Among the main practices influencing soil microbial communities, the application of organic amendments, such as compost, and the management of livestock grazing stand out as key regulators of resource availability, soil structure, and microsite heterogeneity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCompost, especially when produced from recycled organic residues, provides a sustained input of organic C and nutrients that nourish soil microorganisms and stimulate key enzymatic activities. These inputs enhance microbial biomass and the activity of enzymes such as β-glucosidase, urease, and phosphatase, which regulate the mineralization of C, N, and P [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The composition and maturity of compost, its C:N ratio, stabilization degree, and biochemical profile, strongly influence microbial diversity and functional capacity. For instance, Garc\u0026iacute;a-Orenes \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] found that compost derived from agricultural residues increased the abundance of \u003cem\u003eActinobacteria\u003c/em\u003e and \u003cem\u003ePseudomonadota\u003c/em\u003e, while Bastida \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] reported that compost application enhanced oxidative enzyme activities involved in the transformation of complex organic matter.\u003c/p\u003e \u003cp\u003eLong-term applications have been shown to improve functional redundancy and resilience within soil microbial communities, maintaining efficient nutrient cycling and improving soil structure and carbon retention [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Through these mechanisms, compost not only enhances short-term nutrient availability but also promotes sustained improvements in biological soil functioning, fertility, and ecosystem stability [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, excessive or poorly managed compost applications can produce counterproductive effects. Over-application may lead to nutrient imbalances, especially P accumulation,, increased soil salinity, or elevated dissolved organic carbon that stimulates transient microbial respiration but accelerates carbon loss [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Immature or unstable composts can temporarily immobilize N, release phytotoxic compounds, or disturb the balance of soil microbial communities [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Thus, the quality, maturity, and application rate of compost are critical factors in maximizing its benefits while minimizing adverse impacts on microbial activity and soil health.\u003c/p\u003e \u003cp\u003eLivestock grazing represents another powerful driver of soil microbial structure and functioning. Through trampling, manure deposition and shifts in vegetation composition, grazing alters soil physical and chemical properties, plant\u0026ndash;microbe interactions and nutrient redistribution [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These processes generate spatial and temporal heterogeneity in the soil environment, shaping microbial community structure, functional diversity, and enzymatic activity. When grazing intensity and livestock type are carefully managed, moderate grazing can stimulate microbial activity and promote nutrient turnover, enhancing processes such as carbon mineralization and nitrogen cycling [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Moreover, differences among livestock species, due to contrasting foraging behaviour, manure characteristics, and grazing patterns, can exert species-specific effects on soil biota and their ecological functions [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConversely, long-term continuous grazing under high stocking densities often degrades soil health. Persistent trampling and nutrient imbalance can reduce soil organic carbon and nitrogen reserves, limit microbial biomass, and disrupt community composition, ultimately compromising soil fertility and ecosystem multifunctionality [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Soil compaction further restricts gas diffusion and water infiltration, while limited organic matter inputs constrain microbial metabolism and enzymatic expression, leading to reduced biogeochemical efficiency [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo mitigate these impacts, the strategic implementation of resting periods or grazing exclusion zones, areas where livestock are temporarily or permanently removed, has proven effective in supporting the recovery of soil structure and biological activity [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, as highlighted by Shu \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] in their global meta-analysis on grazing exclusion and soil microbiomes, our understanding of how the duration, frequency, and timing of resting periods affect microbial succession, enzymatic functioning, and long-term soil fertility remains limited. Their study demonstrates that while grazing exclusion generally promotes microbial recovery, the magnitude and direction of these effects vary considerably with exclusion duration, grassland type, and climatic conditions. Shu \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] emphasized that the ecological mechanisms underpinning these variations are still poorly resolved, particularly regarding how intermittent or rotational exclusion regimes influence microbial resilience and nutrient-cycling efficiency. Consequently, further long-term, mechanistic research is urgently needed to clarify the temporal dynamics of microbial responses to different grazing-rest strategies and to optimize their role in restoring soil functionality and ecosystem sustainability. As a result, there is an urgent need for long-term, mechanistic studies to clarify the temporal dynamics of microbial responses to different grazing\u0026ndash;rest strategies and to optimize their role in restoring soil function and ecosystem sustainability.\u003c/p\u003e \u003cp\u003eBuilding on this knowledge gap, an additional layer of complexity emerges when considering how grazing-rest strategies interact with other management practices. Despite growing evidence on the independent effects of compost application and grazing, their combined influence on soil microbial communities and enzymatic functioning remains largely unresolved. In Mediterranean agroecosystems, where organic amendments and mixed livestock systems are increasingly common, clarifying these interactions is essential for designing effective soil regeneration strategies that integrate both grazing management and organic inputs.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to examine how livestock management and compost addition shape soil microbial diversity, community structure and functional activity in an olive organic cultivation area. Specifically, we pursued the following objectives: 1) To assess the effects of different livestock management regimes (ovine grazing, equine grazing, and grazing exclusion) on bacterial, fungal and arbuscular mycorrhizal diversity and community composition 2) To evaluate the impact of compost addition on microbial diversity and composition, and to determine whether its influence differs across livestock management types. 3) To quantify changes in soil enzymatic activities related to C, N and P cycling in response to compost addition and livestock presence. 4) To identify specific microbial phylotypes associated with compost addition within each livestock regime, thereby determining whether grazing history modulates microbial indicators of organic amendment inputs.\u003c/p\u003e \u003cp\u003eWe hypothesize that the response of soil microbial communities and enzymatic activities to compost addition is strongly modulated by livestock management, with grazing regime determining the extent to which compost can enhance microbial diversity, functional structure and nutrient-cycling processes. Specifically, we anticipate that soils under ovine grazing will show more pronounced shifts in microbial structure and enzymatic activities in response to compost addition compared to equine grazing or grazing exclusion, reflecting the cumulative influence of more intensive grazing on soil biotic and abiotic conditions.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Experiment design\u003c/h2\u003e \u003cp\u003eThe Cortijo el Puerto farm, located in Lora del R\u0026iacute;o (Seville, Spain), was chosen as the site for soil sampling used in a container trial. The property covers an area of 220 hectares, mainly devoted to olive (\u003cem\u003eOlea europaea\u003c/em\u003e) cultivation in hedgerow systems. The dominant varieties are \u003cem\u003eArbosana\u003c/em\u003e and \u003cem\u003eArbequina\u003c/em\u003e, arranged in a 5 m \u0026times; 1.5 m planting layout, resulting in a density of about 1,200 trees per hectare. Irrigation is supplied through drip lines placed beneath each tree row, with water distribution managed under the authorization of the Guadalquivir Hydrographic Confederation. The farm operates under organic farming standards, emphasizing sustainable and eco-friendly practices.\u003c/p\u003e \u003cp\u003eA no-till approach is implemented, and livestock, specifically donkeys and sheep, assist in controlling ground vegetation. The area experiences a Mediterranean climate, characterized by mild winters and hot, dry summers. Average minimum and maximum temperatures range from 2.6\u0026deg;C in January to 33.8\u0026deg;C in August, and the mean annual precipitation is approximately 475 mm.\u003c/p\u003e \u003cp\u003eThe soil at the site is classified as an Entisol, Typic Xerofluvent (Soil Survey Staff, 2006) with a sandy clay loam texture (28% clay, 27% silt, and 44% sand, according to the USDA classification). The soil presents a pH of 8.0, an organic carbon content of around 4%, and nutrient levels of 4 g kg⁻\u0026sup1; nitrogen, 45 mg kg⁻\u0026sup1; P, and 250 mg kg⁻\u0026sup1; potassium (K). The experimental design comprised three delimited and fenced areas with different livestock management: (1) livestock exclusion, (2) equine, and (3) ovine livestock (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The livestock exclusion area, covering approximately 35 hectares, has been maintained free of grazing for six months.\u003c/p\u003e \u003cp\u003eThe livestock-managed areas have been subject to rotational grazing since 2016, following the sowing of native legumes and grasses in 2015. The ovine area encompasses approximately 75 ha and is grazed by around 150 sheep (2 sheep/ha), specifically of the \u003cem\u003eChurra, Merina\u003c/em\u003e and \u003cem\u003eLebrijana\u003c/em\u003e breeds. The equine area covers about 10 ha and is grazed by 15 adult Andalusian donkeys.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Soil sampling and compost characteristics\u003c/h2\u003e \u003cp\u003eIn June 2023, initial soil samples (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4) were taken from the surface layer (0\u0026ndash;15 cm) at randomly selected points within three experimental plots, approximately 25 cm from the tree trunks and irrigation drippers, using an auger for subsequent DNA and enzyme analyses.\u003c/p\u003e \u003cp\u003eAdditionally, for the compost-application assay, about 3 kg of soil per sampling area were obtained by combining portions collected with a hoe from six different locations within each livestock area. The soil was homogenized, and coarse fragments were manually removed. These composite samples were transported to the laboratory and placed into containers (approximately 450 cm\u0026sup2; each). Compost was applied at a rate of 20 t ha⁻\u003csup\u003e1\u003c/sup\u003e and incorporated into the upper soil layer by manual mixing. The containers were kept outdoors to simulate natural field conditions. After six months, in November 2023, soil subsamples (n\u0026thinsp;=\u0026thinsp;3) were collected from the 0\u0026ndash;15 cm layer of each container for DNA and enzyme analyses, allowing comparison with the initial field samples.\u003c/p\u003e \u003cp\u003eThe compost was produced entirely with by-products from the organically managed farm, following circular economy principles. A 2:1:1 mix of olive mill waste (alperujo), pruning residues, and sheep manure underwent a complete composting process, including a thermophilic phase (\u0026gt;\u0026thinsp;55\u0026deg;C for over 15 days), to stabilize organic matter and ensure pathogen elimination. A detailed description of the compost used can be found in Gil-Mart\u0026iacute;nez \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Soil enzyme activities analysis\u003c/h2\u003e \u003cp\u003eThe potential activity of four different hydrolytic enzymes involved in C, N and P cycling was assayed fluorometrically with a microplate reader (FLUOstar\u0026reg; Omega) using 4-methylumbelliferone (MUF) or 7-amino-4-methyl coumarin (AMC) linked-substrates: β-glucosidase, N-acetyl-β-D-glucosaminidase, acid phosphatase and leucine-aminopeptidase, following the methods described in [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Likewise, two enzymes, dehydrogenase and urease were assayed by absorbance-based methodology. Thus, dehydrogenase activity (DHA) was determined according to Trevors [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] after soil incubation with p-iodo nitrotetrazolium chloride (INT) and measurement of the p-iodo-nitrotetrazidin formazan (INTF) absorbance at 490 nm. Urease activity was determined according to the method proposed by Kandeler and Gerber [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 DNA extraction\u003c/h2\u003e \u003cp\u003eTotal DNA was extracted with DNeasy\u0026reg; PowerLyzer\u0026reg; PowerSoil Kit\u0026reg; (Qiagen Inc.) following manufacturer\u0026acute;s instructions. Library preparation and Illumina sequencing were carried out at the IPBLN Genomics Facility (CSIC, Granada, Spain). Soil-extracted DNAs were quantified and normalized to 5 ng/\u0026micro;l. Amplicon libraries targeting the bacterial 16S rRNA gene, fungal ITS1 and arbuscular mycorrhizal fungi 18S regions were generated by a two-steps PCR strategy. Gene-specific amplification was performed in triplicate with 5\u0026ndash;15 ng of DNA in a final volume of 10 \u0026micro;l. Gene specific primers were: ProV3V4fw (5'-CCTACGGGNBGCASCAG-3')/ ProV3V4rev (5'-GACTACNVGGGTATCTAATCC-3') [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] for bacteria and archaea community; fITS7fw (5'-GTGARTCATCGAATCTTTG-3') [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and ITS4rev (5'-TCCTCCGCTTATTGATATGC-3') [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] for ITS2 region and NS31fw (5'-TTGGAGGGCAAGTCTGGTGCC-3') [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] /AML2rev (5'-GAACCCAAACACTTTGGTTTCC-3') [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] for 18S region, were designed with Nextera overhang adapters. Primers were used at a final concentration of 0.2 \u0026micro;M and reaction was performed with 1X KAPA HiFi HotStart ReadyMix DNA polymerase (Roche Diagnostics, West Sussex, United Kingdom). Cycling conditions were 95\u0026deg;C/3 min, (95\u0026deg;C/30 s, 55\u0026deg;C/30 s, 72\u0026deg;C/30 s) x 25 cycles and then 72\u0026deg;C/5 min for 16S amplification; 95\u0026deg;C/3 min, (95\u0026deg;C/30 s, 57\u0026deg;C/30 s, 72\u0026deg;C/30 s) x 27 cycles and then 72\u0026deg;C/5 min for ITS2 amplification and 95\u0026deg;C/3 min, (95\u0026deg;C/30 s, 65\u0026deg;C/30 s, 72\u0026deg;C/30 s) x 31 cycles and then 72\u0026deg;C/5 min for fungal 18S amplification. Triplicates were pooled together and validated through visualization on a 1.8% (w/v) agarose gel.\u003c/p\u003e \u003cp\u003eAt this stage, amplicons were purified using NucleoMag\u0026reg; NGS Clean-up and Size Select Kit (Macherey-Nagel, D\u0026uuml;ren, Germany) and subjected to a final indexing PCR step using Nextera XT v2 index kit in order to introduce dual combinatorial indices and Illumina sequencing adapters. Cycling conditions were 95\u0026deg;C/3 min, (95\u0026deg;C for 30 s, 55\u0026deg;C for 30 s, 72\u0026deg;C/30 s) x 8 cycles and then 72\u0026deg;C/5 min. 2 additional PCR cycles were applied to 18S amplicon for a total of 10 indexing cycles. Amplicon generation was validated again through visualization on a 1.8% (w/v) agarose gel and cleaned with NucleoMag\u0026reg; NGS Clean-up and Size Select Kit (Macherey-Nagel). Concentration was measured on the Infinite\u0026reg;200 microplate reader fluorimeter (Tecan Trading AG, Switzerland,). Libraries from each analyzed region (16S, ITS2, and 18S) were combined in an equimolecular manner rendering three library pools. Final pools were run on a Bioanalyzer HS DNA chip to verify quality and size distribution, followed by Qubit\u0026reg; (Thermo) quantification, and then diluted and denatured as recommended by Illumina MiSeq library preparation guide. The 300x2 nt paired-end sequencing was conducted on a MiSeq sequencer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Bioinformatics analysis of microbial communities\u003c/h2\u003e \u003cp\u003eBioinformatic analyses were conducted to obtain high-quality bacterial, fungal, and mycorrhizal sequences. Sequence analysis was performed with \u003cem\u003edada2\u003c/em\u003e v1.26.0 R package [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] which allows for the identification of amplicon sequence variants (ASVs), distinguishing true biological variation from sequencing errors and PCR artefacts [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. After removing chimeras, artificial DNA sequences created during PCR, taxonomy was assigned using the SILVA v138.2 database [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] for 16S reads, the UNITE v10.0 database [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] for ITS reads, and the PR2 5.1.0 database [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] for 18S reads. A total of 1,531,671 good quality bacterial sequences, averaging 66,594\u0026thinsp;\u0026plusmn;\u0026thinsp;19,603 sequences per sample, 1,248,392 fungal sequences, averaging 49,936\u0026thinsp;\u0026plusmn;\u0026thinsp;22,819 per sample, and 1,289,644 mycorrhizal sequences, averaging 56,071\u0026thinsp;\u0026plusmn;\u0026thinsp;24,386 per sample, were obtained. Bacterial reads accounted for 99.732\u0026thinsp;\u0026plusmn;\u0026thinsp;0.159% abundance, so from now on we will refer to the 16S community as bacterial community. Similarly, in the 18S dataset, all the sequences presenting arbuscular mycorrhizal primary lifestyle, according to the FungalTraits v1.2 database [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], belonged to the \u003cem\u003eGlomeromycotina\u003c/em\u003e Order, and thus were retained for further analysis representing 83.916\u0026thinsp;\u0026plusmn;\u0026thinsp;15.985% of the total abundance.\u003c/p\u003e \u003cp\u003eDiversity indices were calculated after rarefaction, repeating the subsampling step 100 times [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Each sample was subsampled to 34,900 bacterial, 21,000 fungal, and 17,700 mycorrhizal reads (Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) and the resulting alpha and beta diversity metrics were averaged. Richness was measured as a representative alpha diversity metric. Differences in community composition across samples (β-diversity) were evaluated with the \u003cem\u003evegan\u003c/em\u003e v2.7-2 R package [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] by calculating Bray-Curtis dissimilarity matrices, and performing non-metric multidimensional scaling (NMDS) to compress dimensionality into two dimensional plots. Then, the associations between enzymatic activities and microbial communities were calculated with the \u003cem\u003eenvfit\u003c/em\u003e function within the \u003cem\u003evegan\u003c/em\u003e package. This function fits the vectors of enzymatic activity to the microbial ordinations (NMDS), with the length of the arrow proportional to the correlation [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Biplots of community ordinations and enzymatic \u003cem\u003eenvfit\u003c/em\u003e vectors were generated to visualize the results.\u003c/p\u003e \u003cp\u003eThen, the phylotypes associated with compost addition (pre- and post- compost samples) were identified using the function \u003cem\u003emultipatt\u003c/em\u003e in the \u003cem\u003eindicspecies\u003c/em\u003e R package using the \u0026ldquo;IndVal.g\u0026rdquo; association value [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In particular, this function studies the association between species patterns and combinations of groups of sites and identifies what species are most likely to be indicators of a given group of sites (here, compost addition). These phylotypes were represented as rings in a phylogenetic tree to emphasise the association between specific taxonomic groups and compost addition. The bacterial (16S sequencues) and mycorrhizal (18S sequences) phylogenetic trees were calculated by aligning sequences with the \u003cem\u003emsa\u003c/em\u003e R package [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and generating a maximum likelihood tree with the \u003cem\u003ephangorn\u003c/em\u003e R package [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] using a GTR\u0026thinsp;+\u0026thinsp;GI model. However, due to the hypervariability in length and composition of the ITS region, it is not amenable to robust multiple alignments and phylogenetic reconstruction beyond the genus level [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Thus, we inferred the putative phylogenetic relationship using the Evolutionary Placement Approach (EPA) using EPA-ng [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] and GAPPA [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] to place our ITS sequences on the T-BAS Fungi v3 reference tree [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Data and statistical analysis\u003c/h2\u003e \u003cp\u003eA two-way ANOVA followed by Tukey\u0026rsquo;s post-hoc test was performed to examine the effects of compost and livestock management or their interaction on alpha diversity metrics and soil enzymatic activities.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Microbial Diversity Responses to Compost and Grazing\u003c/h2\u003e \u003cp\u003eBacterial alpha diversity was unaffected by compost addition or livestock presence, whereas compost addition affected fungal diversity, and livestock groups affected both fungi and mycorrhizal communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Fungal alpha diversity was lowest in the exclusion zone compared to the equine zone, a pattern that was similarly observed in mycorrhizal communities. Compost addition significantly reduced fungal alpha diversity (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), as well as homogenized microbial communities, specially within each livestock group (Supplementary Figure S2). Fungal and mycorrhizal communities across livestock groups were further homogenized by compost addition (Supplementary Figure S2). These contrasting responses between bacteria and fungi align with previous findings showing that fungal communities are generally more sensitive than bacterial ones to changes in plant-derived resources, disturbance intensity, and organic matter quality [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The lack of response of bacterial alpha diversity to either compost addition or livestock presence aligns with previous studies showing that bacterial richness tends to be relatively resistant to short-term management changes, likely due to high functional redundancy and broad ecological tolerance [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In contrast, the observed sensitivity of fungal and mycorrhizal diversity to both compost and grazing management supports the idea that these groups are more responsive to shifts in substrate availability and soil disturbance. Xu \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] demonstrated that grazing strongly modulates the structure and carbon-related functional associations of fungal communities in grasslands, emphasizing that fungi, particularly mycorrhizal taxa, respond more tightly than bacteria to herbivore-driven changes in plant inputs and soil microhabitats.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe lower fungal and arbuscular mycorrhizal fungi (AMF) diversity in the exclusion zone compared with the equine plots suggests that moderate grazing may promote microhabitat heterogeneity, root turnover, and organic inputs that favour diverse fungal assemblages. This pattern is consistent with Eldridge \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], who reported that grazing enhances spatial heterogeneity in soil microbial networks by altering plant community structure and nutrient redistribution. The reduction in fungal diversity (alpha and beta) following compost addition indicates that organic inputs may select for specific fungal guilds adapted to the decomposition of nutrient-rich substrates, potentially reducing overall community evenness. Similar declines in fungal diversity after organic amendments have been reported in other grassland systems, where compost inputs tend to favour copiotrophic fungal taxa [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBacterial, fungal, and mycorrhizal communities presented distinct compositional patterns among livestock groups and between pre- and post-compost samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). PERMANOVA analyses confirmed that livestock management was the main factor explaining the largest proportion of community variation across all microbial groups (R\u0026sup2; = 0.27\u0026ndash;0.30, p\u0026thinsp;=\u0026thinsp;0.001). Nonetheless, compost application also exerted a significant influence on community structure in all cases (R\u0026sup2; \u0026asymp; 0.16\u0026ndash;0.18, p\u0026thinsp;=\u0026thinsp;0.001). Moreover, a significant interaction between both factors was detected for bacteria (p\u0026thinsp;=\u0026thinsp;0.023), fungi (p\u0026thinsp;=\u0026thinsp;0.002), and mycorrhiza (p\u0026thinsp;=\u0026thinsp;0.006), indicating that the compositional shifts following compost addition varied among livestock regimes. The fact that livestock explained the largest proportion of variation across all microbial groups is consistent with the growing evidence that herbivore identity and grazing intensity are major drivers of belowground microbial assembly via changes in plant community composition, nutrient cycling, and physical disturbance [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Compost effects, in contrast, tend to be shorter-lived and primarily linked to resource pulses that temporarily shift microbial activity and composition [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. However, the significant interaction between compost and livestock management further suggests that the microbial response to organic inputs is context-dependent, modulated by grazing-induced differences in soil structure, resource availability, and microbial baseline composition. Likewise, Zeng \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] also showed that soils with different grazing histories respond differently to nutrient additions, indicating that grazing legacies can modulate how microbial communities react to new resource inputs. Similarly, Ingram \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] demonstrated that different herbivore species create distinct patterns of organic matter deposition and soil disturbance, which in turn condition subsequent microbial responses to additional organic amendments.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Comparative phylogenetic profiles of microbial communities with compost and livestock presence\u003c/h2\u003e \u003cp\u003eAlthough bacterial alpha diversity remained unchanged across compost treatments and livestock groups, the community underwent a substantial reorganization of specific phylotypes. Distinct distributions were observed in response to compost addition (pre- and post-) across the different livestock regimes (exclusion, equine, and ovine), indicating that shifts in community composition can occur without affecting overall richness. \u003cem\u003eChloroflexota\u003c/em\u003e and \u003cem\u003eActinomycetota\u003c/em\u003e were characteristic of the pre-compost time (dark segments) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In contrast, \u003cem\u003eBacteroidota\u003c/em\u003e was more representative of the post-compost phase (light segments), consistent with taxa typically involved in the degradation of more stabilized organic substrates. These findings align with broader ecological evidence showing that \u003cem\u003eActinomycetota\u003c/em\u003e and \u003cem\u003eChloroflexota\u003c/em\u003e are often more prevalent in low-input or resource-limited soils. For example, long-term studies in grasslands without heavy nutrient additions have found high relative abundances of \u003cem\u003eActinobacteriota\u003c/em\u003e (~\u0026thinsp;40%) under oligotrophic conditions [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Similarly, non‑cultivated soils in the Argentine Pampas exhibited elevated proportions of both \u003cem\u003eActinobacteria and Chloroflexi\u003c/em\u003e, in contrast to fertilized, intensively managed fields [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], a pattern consistent with an oligotrophic life-history strategy. On the contrary, Joos \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] observed that soils amended annually with compost showed a marked increase in \u003cem\u003eBacteroidota (Bacteroidetes\u003c/em\u003e), supporting the idea that these copiotrophic taxa are preferentially stimulated by organic resource inputs.\u003c/p\u003e \u003cp\u003eThe bacterial phylogenetic profiles observed in each livestock regime,exclusion, equine, and ovine,were distinct, indicating that each grazing zone creates a unique set of ecological conditions shaping microbial assemblages. This pattern shows that compost inputs and livestock type interact to restructure bacterial communities at the phylum level without necessarily affecting overall richness, highlighting the combined influence of resource availability and herbivore identity on soil microbial composition [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA similar but clearer pattern of differential occurrence was observed in the fungal communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Studies show that fungal communities may be more sensitive than bacteria to both grazing and compost addition because of their ecological traits and structural dependencies. For example, fungi depend on hyphal networks to explore soil microsites, making them more vulnerable to changes in porosity, moisture, or soil structure [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Moreover, fungi respond strongly to the degradability of organic inputs: more processed or stabilized carbon sources trigger greater shifts in fungal composition than in bacterial communities [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Specific fungal classes were more frequently detected in either pre- or post-compost samples, with \u003cem\u003eDothideomycetes\u003c/em\u003e, \u003cem\u003eEurotiomycete, Glomeromycetes\u003c/em\u003e, \u003cem\u003eTremellomycetes\u003c/em\u003e showing higher representation in pre-compost samples, while \u003cem\u003eAgaricomycetes, Pezyzomicetes\u003c/em\u003e and \u003cem\u003eSordariomycetes\u003c/em\u003e appeared predominantly in post-compost samples. This shift likely reflects the response of fungi to changes in resource availability, as compost inputs promote decomposer taxa (e.g., \u003cem\u003eAgaricomycetes, Sordariomycetes\u003c/em\u003e), a pattern also observed in black soil systems [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] and consistent with the functional ecology described by Fernandez \u0026amp; Kennedy [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNotably, the exclusion samples exhibited the most distinctive fungal profile, characterized by a reduced presence of \u003cem\u003eSordariomycetes\u003c/em\u003e, one of the most abundant classes in equine and ovine plots. \u003cem\u003eSordariomycetes\u003c/em\u003e include many saprotrophic and plant-associated fungi that play key roles in decomposition of organic matter, nutrient cycling, and plant-fungal interactions [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Their lower abundance in ungrazed plots suggests that the absence of grazing may limit the availability of suitable substrates or microhabitats necessary for their establishment or persistence. Such patterns are consistent with co‑occurrence network studies showing that fungal networks are more dynamic and fragile under disturbance or altered environmental conditions, such as grazing exclusion, compared to bacterial networks [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Together, these observations indicate that grazing not only influences fungal abundance but also contributes to the stability and connectivity of soil fungal communities.\u003c/p\u003e \u003cp\u003eRegarding AMF, genera such as \u003cem\u003eGlomus\u003c/em\u003e were characteristic of the pre-compost stage across all livestock groups, whereas \u003cem\u003eFunneliformis\u003c/em\u003e appeared to be enhanced by compost addition (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This pattern suggests that \u003cem\u003eGlomus\u003c/em\u003e may be adapted to more oligotrophic or undisturbed soil conditions, persisting under baseline nutrient availability, while \u003cem\u003eFunneliformis\u003c/em\u003e responds positively to increased organic inputs, likely due to its capacity to exploit enriched nutrient conditions [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. These shifts highlight that AMF communities are sensitive to changes in resource availability and can rapidly reorganize in response to organic amendments, complementing the compositional changes observed in bacterial and fungal communities. Furthermore, the relatively compact clustering of AMF communities in ordination analyses suggests that livestock presence may have a stronger influence than compost on AMF composition, reflecting their dependence on plant hosts and root distribution patterns shaped by grazing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Linking Microbial Composition with Functional Enzyme Responses to Organic Inputs and Livestock\u003c/h2\u003e \u003cp\u003eThe addition of compost produced marked but contrasting shifts in soil enzyme activities. Urease activity declined by 64% across all livestock regimes, whereas glucosaminidase increased by 63% (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), indicating that compost selectively stimulates some N-cycling pathways while suppressing others. These divergent responses align with evidence that organic inputs can reorganize microbial communities and modify nutrient-cycling functions in non-uniform ways [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Consistent with previous findings, our results indicate that compost enhanced specific N-linked hydrolytic activities (e.g., glucosaminidase), whereas enzymes directly related to inorganic N turnover, such as urease, exhibited more variable responses. This highlights that the microbial functional shifts induced by compost are modulated by environmental and substrate-dependent factors.\u003c/p\u003e \u003cp\u003ePhosphatase activity declined markedly, by roughly two-, five-, and six-and-a-half-fold in exclusion, equine, and ovine plots, respectively. While compost typically increases phosphatase activity through its effects on microbial growth and organic P turnover [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], elevated P availability can downregulate enzyme synthesis via feedback inhibition, leading to reduced phosphatase expression despite organic amendments [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Thus, our results likely reflect context-dependent responses, where compost enriched P availability may have downregulated phosphatase activity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLivestock management exerted a distinct influence on other enzymes, most notably β-glucosidase, which reached its highest values in exclusion plots and declined by 40% and 68% in equine and ovine soils, respectively, regardless of compost addition. These patterns highlight the suppressive effect of grazing on cellulose-degrading activity, likely linked to plant biomass removal and shifts in detrital inputs. Dehydrogenase and aminopeptidase activities were shaped by the interaction between compost and livestock presence: Dehydrogenase increased strongly in equine soils (+\u0026thinsp;77%), more moderately in exclusion plots (+\u0026thinsp;33%), but decreased in ovine soils (\u0026minus;\u0026thinsp;17%); aminopeptidase showed a similar trend, increasing by 67% in equine and exclusion soils yet declining by 16% in ovine plots. These interaction effects emphasize that microbial responses to organic amendments are tightly modulated by grazing-induced differences in soil structure, nutrient inputs, and baseline microbial composition, an interpretation supported by studies showing that compost effects vary depending on initial soil microbial networks and environmental context [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe shits in enzymatic activity profiles were mirrored by corresponding functional associations in the microbial communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Prior to compost addition, bacterial assemblages in equine and ovine zones clustered with urease and phosphatase, suggesting active N- and P-cycling under grazing [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In contrast, exclusion plots aligned more closely with β-glucosidase, reflecting enhanced cellulose degradation in the absence of herbivory, which resonates with evidence from Ding \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] that grazing strongly influences β-glucosidase dynamics and microbial network complexity. After compost addition, the only strong association that persisted was between exclusion soils and aminopeptidase activity, suggesting a shift toward protein-degradation pathways. This result is consistent with meta-analytic evidence showing that grazing exclusion generally enhances N-acquiring enzyme activities, including proteases and aminopeptidases, due to reduced physical disturbance and increased accumulation of organic substrates that stimulate microbial protein breakdown [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. In our case, the combination of higher organic N supplied by compost and the favourable microenvironment of ungrazed soils likely promoted peptide-degrading microbial taxa, explaining the distinct post-compost functional signature observed in exclusion plots.\u003c/p\u003e \u003cp\u003eFungal communities exhibited somewhat clearer functional separation than bacteria along the Deh, aminopeptidase, and glucosaminidase axes in compost-treated samples, although the differences were moderate rather than pronounced. This pattern suggests that fungi respond to changes in organic matter inputs and nutrient availability with slightly greater sensitivity than bacteria, reflecting their role in organic N and C turnover [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Dehydrogenase and aminopeptidase activities likely capture fungal oxidative metabolism and protein degradation, while glucosaminidase reflects chitin turnover and fungal biomass dynamics. Together, these functional trends indicate that compost stimulates fungal activity and alters community\u0026ndash;enzyme associations more noticeably than in bacterial communities, but the effect is moderate, highlighting fungi as sensitive but not overwhelmingly dominant responders to organic amendments [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAMF communities, in turn, displayed comparatively compact functional structures, with significant correlations restricted to phosphatase and aminopeptidase (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC), suggesting that AMF traits contribute modestly but consistently to P and N-related nutrient cycling. his functional role is supported by evidence that AMF can mobilize both phosphate and organic nitrogen via hyphal uptake [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Importantly, the functional clustering of AMF in our study was more strongly determined by livestock presence than by compost addition: ovine soils were positioned furthest from enzyme vectors, consistent with weaker AMF involvement in nutrient mobilization under sheep grazing. This is in line with findings from Li \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], who reported grazing-induced shifts in AMF community composition in wetland soils, as well as conceptual work showing that grazing intensity can reshape AMF foraging structures and network interactions [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Overall, our results underscore that compost stimulates nutrient-cycling pathways, but the magnitude and direction of AMF functional shifts depend critically on grazing context and herbivore identity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eOur findings show that grazing management and compost addition have distinct but interrelated effects on soil microbial diversity, composition, and function in Mediterranean olive agroecosystems. Bacterial richness remained relatively stable across treatments, whereas fungal and mycorrhizal communities were highly sensitive to livestock type and organic inputs, making them valuable early indicators of soil management impacts. Herbivore identity and presence explained a large portion of microbial composition, reflecting the central role of grazing-mediated changes in plant inputs, soil microhabitats, and disturbance regimes. The addition of compost further modified community composition and consistently homogenized microbial communities. Associations between microbial composition and enzyme profiles indicate that organic fertilizers do not act uniformly but are highly dependent on the grazing context in which they are applied. Taken together, these results suggest that effective soil restoration and nutrient cycle management in olive agroecosystems require the integration of composting strategies with grazing practices. Considering the identity of herbivores and grazing intensity will be essential to predict microbial responses and maximize the functional benefits of organic fertilizers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eE.M., P.M., L.L.dS. developed the original idea, designed the research and coordinated all field and laboratory operations. Field data were collected by E.M., P.M and L.L.dS. Data gathering was conducted by M.dC., L.L.dS. Laboratory analyses were carried out by E.M., P.M and L.L.dS. Data analysis was performed by M.dC., and L.L.dS. The manuscript was written by M.dC., and L.L.dS and with substantial contributions from all coauthors.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis study was supported by the projects TED2021-130964B-I00 from the Spanish Ministry of Science and Innovation (MCIN), the State Research Agency (AEI), and the European Union \u0026ndash; NextGenerationEU/PRTR, under the projects \u0026ldquo;Biocompost and cover crops: linking soil health, circular economy and cost effectiveness in ecological Mediterranean orchards\u0026rdquo; (Bioecover). Additional support was provided through the Jos\u0026eacute; Castillejo Mobility Grant for Young Researchers, under the project \u0026ldquo;Changes in carbon dynamics in response to the application of organic amendments and sustainable livestock management in Mediterranean organic crops\u0026rdquo;.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKiprotich K, Muema E, Wekesa C, Ndombi T, Muoma J, Omayio D, Tarus J (2025) Unveiling the roles, mechanisms and prospects of soil microbial communities in sustainable agriculture. 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Roles of arbuscular mycorrhizal fungi on soil fertility: contribution in the improvement of physical, chemical, and biological properties of the soil. Frontiers in fungal biology, 3, 723892. https://doi.org/10.3389/ffunb.2022.723892\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi ZF, L\u0026uuml; PP, Wang YL, Yao H, Maitra P, Sun X (2020) Response of arbuscular mycorrhizal fungal community in soil and roots to grazing differs in a wetland on the Qinghai-Tibet plateau. PeerJ 8:e9375. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7717/peerj.9375\u003c/span\u003e\u003cspan address=\"10.7717/peerj.9375\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Grazing management, organic amendment, fungal and AMF diversity, soil enzymes, soil functioning","lastPublishedDoi":"10.21203/rs.3.rs-8364916/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8364916/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGrazing modifies soils through trampling, nutrient redistribution, and changes in vegetation, while compost supplies organic matter and nutrients. Yet how these factors interact to shape soil microbial diversity, composition, and functioning remains unclear. We assessed bacterial, fungal, and arbuscular mycorrhizal (AMF) communities, together with soil enzymatic activities, under three livestock regimes (exclusion, equine, ovine) before and after compost addition in a Mediterranean olive orchard. Bacterial diversity showed no significant changes across treatments, whereas fungal and AMF diversity responded more strongly. Fungal richness differed among livestock regimes, with lowest values in exclusion plots, and both fungi and AMF declined following compost addition. These trends contrasted with the stability of bacterial richness, indicating taxon-specific sensitivity rather than uniform effects of grazing or compost. Livestock regime was the main driver of microbial composition (R\u0026sup2; = 0.27\u0026ndash;0.30), while compost induced significant but secondary shifts (R\u0026sup2; \u0026asymp; 0.16\u0026ndash;0.18). Interactive effects occurred in all microbial groups, and distinct bacterial, fungal, and AMF phylotypes characterized pre- and post-compost conditions. Compost promoted copiotrophic bacterial taxa and decomposer fungal classes. Enzymatic responses were divergent: urease decreased by 64%, glucosaminidase increased by 63%, and phosphatase declined two- to six-fold after compost addition. Grazing reduced β-glucosidase activity by 40\u0026ndash;68%, and compost\u0026ndash;livestock interactions shaped dehydrogenase and aminopeptidase patterns.\u003c/p\u003e \u003cp\u003eOverall, organic inputs and herbivore identity jointly influence soil microbial assembly and nutrient cycling. These findings underscore the need to consider grazing context when evaluating compost as a strategy to enhance soil health in Mediterranean agroecosystems.\u003c/p\u003e","manuscriptTitle":"Livestock management and compost addition shape soil microbial communities and enzymatic activities in Mediterranean agroecosystems","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-23 18:18:01","doi":"10.21203/rs.3.rs-8364916/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9fd5f55d-ad5c-420f-9f76-36525913674b","owner":[],"postedDate":"December 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-03T16:26:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-23 18:18:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8364916","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8364916","identity":"rs-8364916","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}