Global change refers to anthropogenic and climate pattern modification. The consequences of these changes are outstanding on aboveground biodiversity. Soil microbiota are key actors in soil processes, contributing significantly to numerous ecosystem services provided by soil. They are involved in the processes of nutrient cycling, organic matter decomposition, or pollutants degradation. Microorganisms are also able to synthesize volatile organic compounds that are secondary metabolites with multiple ecological roles and mechanisms of action—generally contributing to plant development. Changes in soil microbiota community could modify either negatively or positively their contribution in soil-provided ecosystem services through their involvement in soil functions that they mediate.

This study investigates soil volatilomics as an innovative approach to assessing the impact of land use on soil quality. This research addresses the critical need for sensitive diagnostic tools to distinguish subtle biochemical variations in soils influenced by different land use management practices. Soil samples were collected along a land use transect in Cluj County. Their volatile organic compounds were extracted by headspace solid-phase microextraction (HS–SPME) followed by a gas chromatography–mass spectrometry (GC–MS) analysis. A multivariate statistical method was used to differentiate the volatilome profile. Among the 106 detected compounds, oxygenated species dominated across all land uses, with the highest concentrations in forest soils (77%), followed by grasslands (71%) and agricultural soils (65%). Principal component analysis revealed distinct clustering patterns, with the first two components explaining 72.8% of the total variance (PC1: 41.7%, PC2: 31.1%). Supervised PLS-DA modeling demonstrated robust land use discrimination, achieving AUC values of 0.868 for agricultural versus forest comparisons and 0.810 for both forest versus grassland and grassland versus agricultural comparisons. The volatilome diversity analysis indicated that grasslands contained the highest number of distinct compounds (64), closely followed by forest soils (63), while agricultural soils showed reduced diversity (51). These key findings revealed distinct volatile signatures, with forest soils exhibiting the highest complexity and agricultural soils demonstrating a more homogeneous profile, whereas grassland soils presented high internal variability. These results underscore the potential of soil volatilome profiling as a sensitive indicator of the effects of land use on soil biochemical processes and support the utility of soil volatilomics in sustainable land management and ecosystem monitoring.

Background: Land use change fundamentally alters soil microbial communities and biochemical processes, yet the integrated effects on rhizosphere microbiome–metabolome networks remained poorly understood. Objective: This study investigated land uses as forest, grassland and intermediary edge shape the rhizosphere biochemical networks of naturally grown Barbarea vulgaris. Methods: Rhizosphere soils of Barbarea vulgaris were analysed for microbial community structure abundance, and metabolomic profile applying phospholipid fatty acid (PLFA) profiling and mass spectrometric untargeted metabolomics (GC–MS/MS and MALDI–TOF/TOF MS). These were coupled with co–inertia analysis to assess microbiome–metabolome interactions. Results: Microbial community analysis revealed significant effects of land use on bacterial community structure (G+/G−, p < 0.001). Untargeted metabolomics identified 248 metabolites, of which 161 were mapped to KEGG pathways. Amino acids and derivatives (21.1%) followed by organic acids (16.8%) were the most representative among identified metabolites. Pathway enrichment analysis revealed coordinated reprogramming of central carbon and nitrogen metabolism across land use gradients, particularly in the amino acid metabolism, TCA cycle, and glycolysis/gluconeogenesis pathways. Microbiome–metabolome coupling analysis revealed distinct correlation patterns between microbial phenotypes and metabolite classes, with forest environments showing the strongest biochemical network integration (RV = 0.91). Edge habitats presented intermediate signatures, supporting their role as transitional zones with unique biochemical properties. Conclusions: The environmental context fundamentally shapes rhizosphere biochemical network organization through coordinated shifts in bacterial community structure and metabolic pathway activity. These habitat-specific metabolic signatures suggest that land use change triggers adaptive biochemical responses that may influence plant performance and ecosystem functioning across environmental gradients.

Introduction: Longan is a perennial crop and profitable export fruit well-suited to the Mekong Delta's climate and soils. Although soil deterioration in longan orchards has been studied, little research has addressed soil bacterial communities and their role in soil health. This study investigated the structure of soil bacterial communities and their associations with soil physicochemical properties in longan orchards.Methods: Soil samples were collected from longan orchards cultivated for 15 (N15), 20 (N20) and 30 years (N30) in Vinh Long Province, Vietnam. High-throughput sequencing of 16S rRNA amplicons was employed to assess bacterial diversity and community composition, followed by correlation analyses with soil properties.Results and Discussion: The dominant bacterial phyla identified across sites included Acidobacteria, Proteobacteria, Chloroflexi, Actinobacteria, and Bacteriodota. Bacterial abundance in these soils was positively correlated with sand, pH, NO₃^- and phosphate solubilizing microorganisms, and negatively correlated with moisture, silt, clay, NH₄⁺, exchangeable potassium and available manganese. Longan orchard soils from all three time periods (N15, N20, N30) had more microbial species in common, than in unique ways. However, time under cultivation was an important factor, with species diversity decreasing with age. The youngest orchards (N15) exhibited the highest number of soil bacterial diversity, followed by decreasing diversity as the orchards aged (N20) and lowest at 30 years (N30). Soil properties exhibited complex and interlinked relationships with soil bacterial phyla. Overall, long-term cultivation of longan orchard soil negatively impacted microbial diversity, potentially altering key properties of soil, hence underscoring the necessity for sustainable soil management to preserve soil health and production.

Urban expansion fragments once-contiguous forest patches, generating pronounced edge gradients that modulate soil physicochemical properties and biodiversity. We quantified how fragmentation reshaped the soil microbiome continuum and its implications for soil carbon storage in a temperate urban mixed deciduous forest. A total of 18 plots were considered in this study, with six plots for each fragment type. Intact interior forest (F), internal forest path fragment (IF), and external forest path fragment (EF) soils were sampled at 0–15, 15–30, and 30–45 cm depths and profiled through phospholipid-derived fatty acid (PLFA) chemotyping and amino sugar proxies for living microbiome and microbial-derived necromass assessment, respectively. Carbon fractionation was performed through the chemical oxidation method. Diversity indices (Shannon–Wiener, Pielou evenness, Margalef richness, and Simpson dominance) were calculated based on the determined fatty acids derived from the phospholipid fraction. The microbial biomass ranged from 85.1 to 214.6 nmol g⁻¹ dry soil, with the surface layers of F exhibiting the highest values (p < 0.01). Shannon diversity declined systematically from F > IF > EF. The microbial necromass varied from 11.3 to 23.2 g⋅kg⁻¹. Fragmentation intensified the stratification of carbon pools, with organic carbon decreasing by approximately 14% from F to EF. Our results show that EFs possess a declining microbiome continuum that weakens their carbon sequestration capacity in urban forests.

Despite the increasing recognition of the role of urban orchard ecosystems in sustainable urban development, the mechanistic understanding of how tree species soil biochemical heterogeneity drives microbial community assembly, the spatial patterns governing microbe-environment interactions, and their collective contributions to ecosystem multifunctionality remain poorly characterized. This study investigated how Prunus species and soil depth affect microbial biodiversity and metabolomic signatures in an urban orchard in Cluj-Napoca, Romania. Soil samples were collected from five fruit tree species (apricot, peach, plum, cherry, and sour cherry) across three depths (0–10, 10–20, and 20–30 cm), resulting in 225 samples. The microbial community structure was analyzed through phospholipid fatty acid (PLFA) profiling, whereas the soil metabolome was analyzed by mass spectrometry techniques, including gas chromatography–mass spectrometry (GC–MS/MS) and MALDI time-of-flight (TOF/TOF) MS, which identified 489 compounds across 18 chemical classes. The results revealed significant tree species-specific effects on soil microbial biodiversity, with bacterial biomarkers dominating and total microbial biomass varying among species. The soils related to apricot trees presented the highest microbial activity, particularly in the surface layers. Metabolomic analysis revealed 247 distinct KEGG-annotated metabolites, with sour cherry exhibiting unique organic acid profiles and cherry showing distinctive quinone accumulation. Depth stratification influenced both microbial communities and metabolite composition, reflecting oxygen gradients and substrate availability. These findings provide mechanistic insights into urban orchard soil biogeochemistry, suggesting that strategic species selection can harness tree species-soil microbe interactions to optimize urban soil ecosystem services and enhance urban biodiversity conservation.