Agricultural Land Management practices and their influence on microbial community composition and biological activity in soil

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Integrated amplicon sequencing and biological properties analysis can provide contextual insights into how management practices shape soil microbial communities. Methods: We conducted a completely randomized sampling study at Agricultural University, Plovdiv, to assess the impact of Lavender Cultivation, Wheat-based Rotation and Unmanaged land, on soil microbial community structure and properties. Results: Taxonomic assessment indicated a clear distinction in microbial community composition. Unmanaged soils were dominated by reduced and less diverse but dominant microbial groups, possibly driven by selection pressure from limited resources. In contrast, cultivated soil supported diverse microbial community of r and k strategists. Enzymatic activity increased significantly (p≤0.05) in managed soil. Land management significantly influenced the pH, EC, Basal Respiration, and Soil Moisture content (p≤0.05). Higher soil respiration (CO2) was observed in uncultivated soil, indicating role of substrate quality in microbial substrate utilization efficiency. Proteobacteria (54.75%) was the dominant phyla in unmanaged land, followed by Bacteroidota (16.45%). In Lavender cultivation, Actinobacteriota (34.20%), Proteobacteria (20.56%), and Acidobacteriota (20.11%) were the most abundant. Similarly, in Wheat based rotation, diverse proportion of Acidobacteriota (28.73%), Actinobacteriota (19.97%), Proteobacteria (17.5%) and Bacteroidota (10.64%) was observed. Alpha diversity indices such as Shannon and Simpson index was higher in cultivated soil. Beta diversity analysis showed a distinct dissimilarity between uncultivated and cultivated soil. Conclusions: Our findings indicate that interaction between factors such as cropping system, fertilization, and moisture content, distinctly shape the microbial community. Long term monitoring would help understand sustained effect on soil health. Land Management Soil Enzyme Relative Abundance Microbial diversity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 INTRODUCTION Land use and management practices are one of the most crucial factors influencing the physical, chemical, and biological properties of soil (Christel et al., 2021 ; Meena & Rao, 2021 ; Maharjan et al., 2017 ; Haghighi et al., 2010 ). It encompasses a range of human activity that directly affect soil health and are important driver of the changes in soil properties as well as microbial community. In addition to factors such as the parent material of the soil and environmental conditions, plant type, soil type, and, crucially, root exudates (Walker et al., 2003 ), these anthropogenic practices shape the functioning of soil mechanisms (Ramesh et al., 2019 ; Weil & Brady, 2017; Drenovsky et al., 2009). Essentially, soil physical, chemical and biological properties are interrelated and together linked to the changes in management practices (Chami et al., 2020 ; Lee et al., 2020 ). The agricultural land system differs from a natural ecosystem in multiple aspects. Here, the influence is elevated since it is highly subjected to disturbance. Unlike natural ecosystems, soil properties in agricultural setting are subject to changes based on cultivation practices (Reilly et al., 2023 ). Particularly, among these, biological properties offer valuable insights to understand evolving state of soil processes, due to their responsive nature to changes in management and environmental conditions (Jat et al., 2018 ). These biological parameters precede observable physiochemical changes in soil, thus serving as a reliable indicator of soil quality (Bhaduri et al., 2022 ; Kennedy & Stubbs, 2006 ). The sensitive response helps monitor the shift in soil property and evaluate the impact of land management strategies and agricultural practices early. Land management practices bring about changes in the microenvironment that regulate both, structure and activity of the soil microbial community (Lupwayi et al., 2017 ). It includes changes in tillage practices, cropping patterns, fertilizer application, cover cropping, soil protection approaches, cropping systems, diversification etc. (Desta et al., 2021 ; Grieve, 2001 ). Specifically, studies conducted to understand the impact of agricultural land use show that interaction through changes in mulching (Djigal et al., 2012 ), no-tillage (Kabiri et al., 2016 ), conventional tillage (Balota et al., 2003), residue incorporation and decomposition (Bending et al., 2002 ), and fertilization (Hamel et al., 2006 ) play influential role on soil biology and soil microbial diversity (Zong et al., 2024 ). Unlike forest or other undisturbed vegetation, under cultivation, the return of the plant litter and residues is less observed, hence reduced carbon and nutrient source changes the dynamics with regards to microbial functioning. The shift in microbial community structure and its role in the distribution of r-strategist, k-strategists, or pathogenic groups needs to be studied to understand the effect of the management strategies. Soil microbial communities are the fundamental driver of soil ecological processes and biogeochemical cycles and are, therefore, essential to overall soil functioning. The microbial community plays an active role in nutrient cycling, organic matter decomposition, biotic and abiotic stress amelioration, respiration, biogeochemical cycle, crop production and other soil functions, which are substantially elevated in the rhizosphere (Griffiths & Philippot, 2013 ; Mendes et al., 2013 ; Bissett et al., 2011 ). Soil microbial populations adopt different life strategies that impact the microbial community structure under varying conditions leading to the dominance of copiotrophic or oligotrophic organisms (Chen et al., 2021 ) which is reflected in other soil processes. Microbial communities, made up of a vast range of preferential microbes, are sensitive to land use and management practices apart from vegetation, aboveground biomass, diversity, soil properties, and environmental changes (Christel et al., 2021 ; Bissett et al., 2011 ; Bengtsson et al., 2005 ). Plant species, above-ground biomass and cropping systems significantly influence soil biology and relative abundance of microbial phyla (Liu et al., 2019; Zhou et al., 2017 ). The association between plants and microbes range from symbiotic and mycorrhizal associations to other detrimental associations (Dolatabadian, 2020 ). Hence, the community structure and its activity are influenced mainly by the rooting structure, quality of plant residue, and release of carbon exudates from the above-ground vegetation. However, the scenario is still unclear in essential oil crops like Lavender. Moreover, comparing the microbial community structure in the same soil and region, under essential oil continuous cropping (Lavender), cereal crop rotation (wheat-maize) and uncultivated areas, can help in the assessment of soil properties, specifically biological properties under these systems. Fertilization affects microbial growth through the availability of nutrients in readily available forms helping microbial proliferation and heightened enzymatic activity (Hardy et al., 2019 ; Chu et al., 2007 ). The association of long-term mineral fertilization, and organic amendments changes the composition of fungal and bacterial groups because of how different groups process the nutrients in the soil (Beauregard et al., 2010 ) and changes the enzymatic activity in soil (Maschner et al., 2003). Under fertilized conditions, major nutrients increase, which positively affects the soil organic carbon, microbial proliferation and plant exudation (Guan et al., 2022 ). Previous studies have documented a decline in organic matter under intensive agricultural cultivation and undermining of microbial diversity (Zhang et al., 2012 ), and since SOC is directly linked to microbial activity, it is pertinent to understand these dynamics as well. On the other hand, inorganic fertilization may help increase the abundance but not the diversity. Under excessive N fertilizer use, bacterial diversity and carbon and nitrogen content are reduced in the soil (Verzeaux et al., 2016 ). In agricultural soils, land management practices elevate loss of soil organic carbon through practices of residue removal and tillage but could stabilize SOC through practices such as cover cropping, zero tillage etc. (Sul et al., 2013 ). Continuous cultivation demands higher nutrients to sustain plant production, which often leads to nutrient depletion, subsequently reducing soil microbial population and its activity. Crop-related factors such as cropping pattern, cropping biomass, crop type, crop rotation (Guo et al., 2024 ), intercropping, and cropping system (Massaccesi et al., 2020 ) shape microbial community due to plant behaviour and litter availability. Cropping diversification has indicated better result in improving soil aggregation, organic carbon, Nitrogen and microbial diversity (Tiemann et al., 2015 ). The biomass changes rhizodeposition and increases exudates rich in low molecular weight carbon-rich compounds, sugars, amino acids, vitamins, etc., that activate microbial enzyme release enhancing soil enzymatic activities (Ma et al., 2025 ). For instance, specific microbial taxa, including Trichoderma and Rhizopus, have been identified as potential bioindicators of these changes (Silvestro et al., 2018 ). In long-term wheat cultivation systems, reductions in nitrogen and phosphorus availability can lead to shifts, favouring groups that adopt slower growth strategies. This restructuring is linked to increased nutrient use efficiency and a decline in microbial biomass carbon (MBC) (Cruz et al., 2009 ). With regards to crop rotation, the key rhizosphere taxa is better at suppressing pathogens compared to a mono-cropping system, which has less diverse microbial abundance possibly due to association with the production of root exudates and compounds (Zhou et al., 2023 ). In Bare soil, the lack of organic input aggravates the situation and has lower soil organic carbon, nutrient availability and low microbial abundance. In case of reduced and lack of Nitrogen fertilization, K strategists might dominate the microbial community (Cruz et al., 2009 ). The strategies are also linked to soil carbon content and the C: N ratio, influencing carbon cycling (Osburn et al., 2024 ; Piton et al., 2023 ). The metabolism of aboveground biomass (C3 or C4), also influences the accumulation of SOC where C4 metabolism may not accumulate high SOC due to quicker decomposition and turnover rate at higher temperatures. (Singh et al., 2019 ; Wand et al., 1999 ). pH could regulate soil microbial composition and enzymatic activities in soil (Zhong et al., 2024), which is again influenced by agricultural practices and quality of organic matter, and breakdown byproducts releasing organic acid, H + ions, and HCO3- ions (Guo et al., 2023 ; Xiao et al., 2022 ; Jones et al., 2009 ). Due to the dynamics between land management, cropping system, and soil biology, the nature of the response of the microbial community necessitates site-specific studies of management practices on soil microbial structure and soil health. The strategies adopted by the microbes present in soil are through multiple pathways of compound production, competition, modification of cellular membrane, metabolites, enzymatic production, or chemical signalling metabolisms etc. (Wang et al., 2023 ). Higher release of simple organic carbon rich compounds from exudates and residue with low C: N ratio might lead to the dominance of microbial groups such as Pseudomonas, β- and the γ- sub-groups of proteobacteria that are copiotrophic in nature and efficiently utilize the compounds. This proliferation thereon can result in organic matter mineralization. On the contrary, microbes such as Ascomycota, Actinobacteria, Deltaproteobacteria, Basidiomycota, and myxobacteria etc., may increase in abundance under nutrient-scarce conditions and degradation of recalcitrant organic matter (Chen et al., 2025 ; Bastian et al., 2009 ; Bernard et al., 2007 ). Practices of no-tillage and retention of residues in the field have been reported to increase organic Carbon and nitrogen levels and soil microbial activity, but the authors also found an increased incidence of pathogenic microbes (Pankhurst et al., 1995 ). Beneficial microbial groups, such as Bacillus, Trichoderma, Pseudomonas, etc., have been isolated and commercially applied to diversify the microbial community (Wang et al., 2023 ; Tao et al., 2020 ). Soil enzymes are sensitive to changes in land management practices, environment and soil properties like pH, organic matter, and nutrient availability (Neemisha & Sharma, 2022; Allison & Vitousek, 2005 ; Dick & Tabatabai, 1993). Enzyme activities are an indication of the biochemical processes and have subsequent effects on the microbial community functioning (Moghimian et al., 2017 ). Both intracellular and extracellular enzymes in the soil, either, after synthesis/secretion by microbes, cell lysis, or stabilized in the soil matrixes, facilitate the chemical catalysis and biochemical breakdown of organic and inorganic compounds in soil matrixes (Nannipieri et al., 2018 ). Hence, although it may provide an indication of the soil's biological activity, we cannot equate it with microbial activity. Therefore, other forms of biological assessment may help in better assessment. For instance, when complex compounds are adequate and simple nutrients are scarce, enzyme production is expected to increase as microbial degradation occurs to access resources. However, enzyme activity may remain low under resource-limited conditions (Allison & Vitousek, 2005 ). Localized studies can investigate the effect of specific management practices and allow for any modifications. Although the application of inorganic fertilizer is associated with an increase in the abundance of the microbial population, it may not have same impact on microbial diversity and richness (Dincă et al., 2022 ). Hence, a combination of assessing biological studies, including enzyme activity and amplicon sequencing, can provide contextual insight into biological health for informed decision-making on long-term management strategies in agricultural soil. Bulgaria's agricultural production is dominated by cereal cultivation, where wheat production is the highest (European Commission, 2023). Similarly, it is the largest producer of lavender worldwide (Stanev et al., 2016 ). European Green Deal aims to make significant changes in the agricultural practices and nutrient management strategies of EU countries (European Commission, 2020a ). Bulgarian agricultural setting provides an opportunity, with limited research on the interaction and influence of soil management and cropping systems on soil biological health, particularly the microbial community. Our study was conducted to study how structural differences in soil microbial communities vary across different agricultural land management systems. It also aims to provide insight into understanding the soil biology in a cereal-based agricultural system (with relatively diversified cropping and fertilization regime), in essential oil crop systems (under monoculture and longer cultivation), and in unmanaged agricultural land use system. MATERIAL AND METHODS Study site This study was conducted in a long term experimental site adjacent to each other in the Research Station of Agricultural University, Plovdiv from 15th of April, 2025 to May 2025 (42°07'45.8"N 24°48'03.9"E). The annual rainfall in Plovdiv is 551 mm with annual average temperature at around 11.4 degree Celsius. Three sites subjected to different agricultural land management practices were selected for studying the influence of agricultural system in the soil microbial community structure and properties. Soil Collection and Soil Sampling Randomized soil sampling approach was used to collect soil samples from each land management system in April 2025. Composite soil samples were collected from the 0 to 20 cm from the soil surface from each site separately, homogenized and packed into sampling bags. Soil samples were collected so as to be representative of the whole field. Once in the laboratory, the sample was air dried, sieved (< 2mm) and stored for further analysis. The fresh soil samples were for stored in refrigerator (-4 ° celsius) for biological analysis and amplicon sequencing. Table 1 Experimental and Management system with their background history Agricultural system Management practices Cropping History Fertilization History Lavender cultivation system Organic farming, inter-row mowing, minimal tillage, weed control Perennial Lavandula angustifolia (5 + years) No synthetic fertilizers; compost or manure applied occasionally Wheat based agricultural rotation Conventional tillage, crop rotation, herbicide and pesticide use Wheat–maize–sunflower rotation over the past 6 years Regular application of NPK fertilizers and urea Unmanaged area with grasses No tillage, no inputs, natural vegetation Dominated by perennial grasses and spontaneous herbs No fertilization Soil pH and Electrical Conductivity 5 gram of air dried soil sample after sieving was taken and mixed with 25 ml of distilled water into 1:5 ratio. The mixture was shaken for 30 minutes and left to settle for 30 minutes. After sedimentation, the sample, was filtered and pH and EC measurements were taken using pH meter and EC meter (Rhoades, 1996 ; Thomas, 1996 ). Growth of Colony forming Units Preliminary probe study was conducted in December 2024 during the winter season to assess the microbial community present in the three sites. Various specialized nutrient media (Table 2) were prepared that catered the growth of differing microbial groups. 1 gram of fresh soil sample was weighted and 99 ml of sterile distilled water was added in a test tube for serial dilution method to form 1:100 ratio. The solution was shaken to mix uniformly and left to settle. Then, 1 ml of the solution was taken in another test tube and mixed with 99 ml of sterile distilled water to prepare dilution of 10 3 , 10 4 , and 10 5 solution. Following this, the sterile media after autoclaving at 121 ° Celsius for 2 hours were plated and left to cool for a few hours. The diluted soil samples were plated in the solidified media under laminar air flow and incubated to observe colony growth. Table 2 Specialized media and their composition Media Specialized growth Composition Rose Bengal Agar Specialized fungal growth Peptone, glucose, KH₂PO₄, MgSO₄, Rose Bengal dye, agar Tryptic soy agar (TSA) Specialized bacterial growth Pancreatic digest of casein, enzymatic digest of soybean meal, NaCl, agar Yeast extract agar Specialized Yeast Growth Yeast extract, peptone, glucose, agar Azotobacter Media N2 fixing Bacteria Growth Glucose, KH₂PO₄, MgSO₄, NaCl, CaCO₃, FeSO₄, agar PKV media Phosphate solubilizing bacteria Growth Glucose, tricalcium phosphate (Ca₃(PO₄)₂), (NH₄)₂SO₄, NaCl, MgSO₄, agar Actinomycetes Specialized Actinomycetes growth Casein, KNO₃, NaCl, MgSO₄, K₂HPO₄, agar Sabouraud dextrose agar Specialized for Fungal and yeast growth Peptone, dextrose (glucose), agar; acidic pH (~ 5.6) to inhibit bacterial growth Dehydrogenase Activity The dehydrogenase activity was estimated following Thalmann (1968) modified by Alef (1995). This estimation of Dehydrogenase activity is based on the reduction of Triphenyl Tetrazolium Chloride (TTC) to Triphenyl formazon (TPF) that is driven by microbes present in the soil sample. 1 grams of fresh soil was taken and placed in a test tube. To this 5 ml of 2,3,5- Triphenyl Tetrazolium Chloride (TTC) solution was added. Blank control was placed which included only 5 ml Tris buffer and no TTC solution. All treatments were replicated 3 times. These test tubes were incubated for 24 hours at 30 ° Celsius. After incubation, 40 ml of acetone was added to each replicates and shaken to mix thoroughly after which the mixture was left at room temperature in the dark for 2 hours. The solution was then filtered and absorbance of the reduced TPF in filtrate was measured using spectrophotometer at wavelength of 546 nm. Special care was taken to conduct procedures under diffused light due to the sensitivity of TTC and TPF. Tris Buffer was prepared by adding 12.114 grams of TRIS and 648 ml of 0.1 M HCl which was made up to 1000 ml using distilled water. β-Glucosidase Activity Beta Glucosidase activity was estimated according to Tatabatai (1982) modified by Alef and Nannipieri (1995). The estimation was based on the degradation of p-nitrophenyl-β-D-glucoside (PNG) to p- nitriphenol through microbe present in the soil. 1 gram of fresh soil was placed in volumetric flask. Then 0.25 ml of toluene was added to the sample following which 4 ml of buffer solution was added. Buffer solution was prepared by mixing from 21.1 g Tris, 11.6 g maleic acid, 14 g citric acid, 6.3 g boric acid, 500 ml of 1 M NaOH, and 1-liter distilled water. To the mixture 1 ml of p-nitrophenyl-β-D-glucoside (PNG) was added. The samples were mixed and then incubated for 1 hour at 37 degree Celsius. Following this, in the incubated soil, 1 ml calcium chloride (CaCl 2 ) and 4 ml of Tris buffer (pH 12) was added and shaken to mix and filtered. The absorbance of the filtrate was then measured with spectrophotometer at 400 nm wavelength. Basal Soil Respiration Rate The basal soil respiration was measured according to Alef (1995). 50 grams of fresh soil after removing organic residues was placed in a Jar. 20 ml of NaOH was measured in a beaker and placed inside the jar carefully without any contact and the lids were sealed. This was replicated 3 times. Similarly, for blank, only NaOH but no soil sample was used and replicated 3 times. The jars were placed in an incubator for 2 hour at 26 degree Celsius. After the exposure time, 1 ml Barium Chloride (BaCl 2 ) was mixed with NaOH that leads to precipitation of carbonates forming Barium Carbonate. A few drops of 0.1% phenolphthalein was added to the mixture and the solution was titrated against 0.05M HCL until the colour changed from violet to colourless. NaOH + CO2 = Na2CO3 + H2O $$\:CO₂\left(mg\right)SW⁻¹t⁻¹=\frac{\left(Vo-V\right)\times\:0.05\times\:22}{dw\:\times\:t}$$ Where, V 0 = amount of HCL required for Blank, V = amount of HCL required in soil, t = Incubation time (in hours), dwt = dry weight of 1g moist soil, 22 = Equivalent weight of Carbon Dioxide (CO 2 ). SW = Dry weight of soil in grams. Genomic Analysis DNA Extraction Genomic DNA was extracted from fresh soil samples using the DNeasy PowerSoil Pro Kit (Qiagen, Germany), following the manufacturer protocol. Approximately 0.25 g of homogenized soil was used for each extraction. To ensure consistency and avoid DNA degradation, all extractions were performed under sterile conditions and stored at − 20°C until downstream processing. The quality and quantity of the extracted DNA were assessed using a NanoDrop™ 2000 spectrophotometer (Thermo Fisher Scientific, USA) and verified by agarose gel electrophoresis. DNA samples with A260/280 ratios between 1.8 and 2.0 and no visible degradation were selected for sequencing. Amplicon Sequencing The V3–V4 hypervariable regions of the 16S rRNA gene were amplified using universal primers 341F (5′-CCTACGGGNGGCWGCAG-3′) and 806R (5′-GACTACHVGGGTATCTAATCC-3′) for bacterial community analysis. PCR reactions were performed for each sample using high-fidelity polymerase (Phusion High-Fidelity DNA Polymerase, New England Biolabs) to minimize amplification errors. The amplicons were purified using AMPure XP beads (Beckman Coulter), and library preparation was performed using the Illumina Nextera XT DNA Library Preparation Kit. Paired-end sequencing (2 × 300 bp) was carried out on the Illumina MiSeq platform at [Novogene, UK], generating high-throughput sequence data for microbial community profiling. Raw sequence reads were demultiplexed, quality-filtered, and processed using the QIIME2 (Quantitative Insights Into Microbial Ecology, version 2024.2) pipeline. Chimeric sequences were removed using DADA2, and the remaining high-quality sequences were clustered into amplicon sequence variants (ASVs). Taxonomic classification was assigned using the SILVA v138 database for bacterial sequences and the UNITE database for fungal sequences. Alpha and beta diversity indices (Shannon, Simpson, Bray-Curtis) were calculated, and community structure differences were visualized through principal coordinate analysis (PCoA) and non-metric multidimensional scaling (NMDS). Phylogenetic distances were assessed using UniFrac metrics to compare microbial community relatedness across different land use systems. Data Availability The raw sequence data generated from this study have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject PRJNA1292883. Metadata files and QIIME2 artifacts are available upon reasonable request to the corresponding author. Statistical Analysis The influence of land management on soil properties were assessed using one way ANOVA to check for significance. The data were checked for normality of distribution using Shapiro-wilk test and Levene’s test was used to check the normality/homogeniety of variance in observed data. Both of these tests were done using package car (Fox et al., 2012 ). Then, in case the assumption of equal variance across group did not meet (i.e. levene test significant meaning the variance in a group is different), data were log transformed, and further analysis were conducted. Subsequently, the multiple comparison of mean between the treatments was further analysed with posthoc test using Tukey Honestly Significant Difference test using agricolae package (Mendiburu, 2019 ). The analysis was conducted at 5% significance level (p ≤ 0.05). All analytical tests were conducted in R Studio version 2024.04.1. The sequencing data were analysed using QIIME2 following standard DADA2 downstream analysis. The plots were prepared using ggplot2 package. RESULTS Soil pH and EC under three land management system The agricultural management system had significant effect on soil pH. Lavender cultivation system exhibited the highest soil pH (7.38 ± 0.0173), followed closely by the wheat-based rotation (7.30 ± 0.0208), with no significant difference between them. The unmanaged area with wild growth showed a significantly lower pH (7.06 ± 0.0656) compared to both managed systems. This suggests that agricultural management, particularly perennial systems like lavender cultivation, may help maintain slightly more alkaline soil conditions, possibly due to organic amendments or reduced nutrient depletion. Likewise, we observed that land management practices had significant impact on the Soil Electrical Conductivity (EC) of the soil. EC was significantly higher in the lavender system (0.178 ± 0.013 mmho/cm). On the other hand, unmanaged grassland (0.142 ± 0.0055 mmho/cm) and wheat-based rotation system (127 ± 0.006 mmho/cm) had similar and significantly lower EC values. Enzyme activities under differing Agricultural Land use Management The influence of land management practices on both Dehydrogenase activity and β-Glucosidase Activity across the sampled sites were significant (p ≤ 0.05). The wheat based rotation exhibited highest dehydrogenase activity (0.489 ± 0.0162) followed by significantly lower Lavender cultivation (0.380 ± 0.0172) and unmanaged land (0.357 ± 0.00885). Table 3 Dehydrogenase and Beta-Glucosidase activity under different Agricultural system Agricultural Land Use system Dehydrogenase Activity (µg TPF/g Soil) β-Glucosidase Activity (µg pNP/g soil) Lavender cultivation system 0.380 ± 0.0172 b 29.3 ± 2.97 a Wheat based Rotation 0.489 ± 0.0162 a 25.8 ± 0.665 ab Unmanaged area 0.357 ± 0.00885 b 14.6 ± 1.57 b The values reported are Mean ± SE and are significant at p ≤ 0.05. With regards to β-Glucosidase Activity, Lavender Cultivation system exhibited high enzymatic activity (29.3 ± 2.97) followed closely by Wheat based rotation (25.8 ± 0.665). The lowest enzymatic activity was observed in unmanaged land (14.6 ± 1.57). Basal Soil Respiration under three Agricultural system Table 4 Basal Soil Respiration and Soil Moisture under different Agricultural system Agricultural Land Use system Basal Soil Respiration rate (mgCO2/gm/hr) Lavender cultivation system 4.59 ± 0.0942 b Wheat based Rotation 4.35 ± 0.0976 b Unmanaged area with wild grass 5.99 ± 0.299 a The values reported are Mean ± SD and are significant at p ≤ 0.05. Different letters indicate significant difference between the means. Similarly, the effect of agricultural system was exhibited in the basal soil respiration with highest CO2 production in unmanaged area with presence of wild grasses (5.99 ± 0.299 a ). The effect of land management on basal soil respiration was significant (p < 0.05). Soil respiration under Lavender monoculture (4.59 ± 0.0942 b ) and wheat based rotation (4.35 ± 0.0976 b ) were significantly lower in comparison to unmanaged area. However, soil respiration under these two system were statistically similar to each other. Microorganisms and Colony Forming Units different Agricultural Land use Management We found significant effect of land management on the growth of soil microbe in artificial media. Among specialized media, phosphate solubilizing bacteria (Pikovskaya’s media) and Nitrogen solubilizing bacteria (Azotobacter media), both exhibited significant impact of land management on their growth habit (p < 0.05). For instance, higher number of microbial growth in Azotobacter media was observed in Wheat based rotation, followed by statistically similar unmanaged area. The lowest colony count was observed in lavender cultivation. Likewise, highest colony growth of phosphate solubilizing bacteria was on Lavender cultivation and Wheat based rotation with lowest record in unmanaged area. Actinomycetes colonies were higher in Wheat based rotation and Lavender cultivation which was statistically higher than unmanaged area. We did not find significant impact of land management in the colony growth on tryptic soy agar (for general bacterial growth) and Sabouraud dextrose agar (fungal growth). Still, with TSA we found higher colonies in Wheat based rotation, and lavender cultivation relatively. In case of Sabouraud, growth was only observed in wheat based rotation, and no growth on other land management. The growth observed in Rose Bengal agar was significantly higher than both wheat based rotation and unmanaged area. Table 5 Colony forming units (CFU) growth under specialized media Colony Forming Units Land Management System Lavender cultivation Wheat based rotation Unmanaged area P value N2 fixing bacterial media (Azotobacter) 3 b 3.74 a 3.39 ab < 0.05, * Actinomycetes 5.113 a 5.13 a 4.74 b < 0.05, * Rose Bengal Agar 3.47 b 4.55 a 3.39 b 0.05, ns Phosphate solubilizing Bacteria Media 5.11 a 5 ab 4.74 b 0.05, ns * indicates significant effect of land management system at p < 0.05. ns = nonsignificant, Differing letter indicates statistically different mean values of measured properties. The culturing of soil microorganisms on specialized media exhibited differing result that indicated the significant influence of land management on colony forming units of soil microbes in artificial media. The N2 fixing bacterial growth media exhibited significantly higher CFUs in Wheat based rotation followed by Unmanaged area (statistically similar but lower) with low colony growth in Lavender (significantly lower). Actinomycetes colony growth was higher and statistically similar in wheat based rotation and lavender cultivated soil whereas it was significantly lower in unmanaged area. Likewise, microbial growth in Rose Bengal agar was also significantly different among the management practices. It was significantly higher in wheat rotation, meanwhile the other two has similar but statistically lower colonies growth. The colony growth of microbes in pikovskaya’s media was higher significantly, significantly high colonies were observed in lavender cultivation. This was followed by statistically similar but lower CFU in wheat based rotation. The lowest colonies of p solubilizing bacteria were present in unmanaged soil. In case of growth in tryptic soy agar, and sabouraud dextrose agar, colony growth were not significantly different among the different land management system. Gravimetric water Content under different land management Table 6 Soil Moisture content of Fresh Soil Under different agricultural system Agricultural Land Use system Soil Moisture Content (%) Lavender cultivation system 21.2 ± 0.208 c Wheat based Rotation 25.4 ± 0.111 b Unmanaged area with wild grass 28.0 ± 0.347 a The values reported are Mean ± SD and are significant at p ≤ 0.05. Meanwhile, Gravimetric Water Content (GWC) of the field soil under differing land management system varied between the soil subjected to these practices significantly (p < 0.005). Highest gravimetric content was observed under unmanaged area with wild grasses (28.0 ± 0.347 a ). This was followed by Wheat based rotation system (25.4 ± 0.111 b ) and Lavender Cultivation system (21.2 ± 0.208 c ). The values reported are Mean ± SD and are significant at p ≤ 0.05. Soil Moisture and its relationship with Basal Soil Respiration The linear regression analysis showcased nonsignificant but positive relationship (R2 = 0.45, p > 0 .05) between the soil moisture content and basal soil respiration. This also showcased distinct differentiation of land use and its moisture content in the soil (Fig. 6). Metagenomic Characterization of Soil Bacterial Community Metagenomic Sequencing and Quality Assessment of the Soil samples All of our soil samples showcased high sequence quality, with over 95% score of Q30. High number or base quality is an indication of reliable base calls (Ewing and Green, 1998). After quality filtering a total of 192381 paired-end reads were clustered into OTUs. The lower number of chimeric reads, and higher number of qualified reads was suitable for metagenomics profiling through downstream analysis. The GC content varied across the samples. It was higher in Lavender Cultivation (57.73%) in comparison to Wheat based rotation (56.13%), with lowest in unmanaged area (53.91%). Relative Abundance of microbial groups under three land management The taxonomic classification was conducted and ten most abundant phyla in each land management were identified and then used to construct a histogram to present their relative abundance in the sample. The representation allows a comparative analysis of the dominant bacterial phyla between these land management systems. We found that the relative abundance varied across the samples (Fig. 10). Proteobacteria (54.75%) was the dominant phyla observed in unmanaged land followed by Acidobacteriota. Incase of Lavender cultivation, Actinobacteriota (34.20%), Proteobacteria (20.56%), and Acidobacteriota (20.11%) were the most abundant phyla with high proportional distribution. This was also similar in Wheat based rotation, where Acidobacteriota (28.73%), Actinobacteriota (19.97%) and Proteobacteria (17.5%) showed a higher proportion but contributed lower to the total relative dominance. This visualization provides and understanding into the distribution and abundance of major bacterial phyla in soils subjected to differing land management practices. At Genus level, among the top 10 abundant genus, Masilia (12.28%), Sphingomonas (7.37%), Pedobacter (5.50%), Pseudomonas (4.45%), Lysobacter (3.10%) were abundant in unmanaged area. However, this distribution in managed area was at a relatively lower percentage in Lavender cultivation and Wheat based rotation. For instance, Gaiella (5.42%), and Sphingomonas (5.19%) were abundant in Lavender based cultivation whereas, this was much lower in wheat based rotation Gaiella (2.07%), and Sphingomonas (2.80%). In wheat based distribution, we found well distributed microbial population while looking at highly abundant 10 genus, occupying over 1% abundance, except for 2 Genus (Fig. 10). Microbial Community Composition across different Land management Similarly, the Venn diagram was created to observe the distribution of shared and unique feature sequences i.e. operational taxonomic units (OTUs) or amplicon sequence variants (ASVs) across different land management practices. The highest feature sequences were observed in Lavender cultivation with 1245 unique feature sequences followed by 1140 unique feature sequences indicating distinct a microbial community presence. The lowest unique feature sequence (871) were present in unmanaged areas. Over all, a total of 4117 OTUs were observed across the three land management systems. A total of 271 feature sequences were shared among the three management system indicating the core microbiome apart from the unique feature sequences. A higher share between wheat based rotation and lavender cultivation was observed with 305 shared features followed by wheat based rotation and unmanaged area (199). Low (86) feature sequences were shared between unmanaged area and lavender cultivation which indicated the distinct differences in microbial community structure between these land management practices. Ternary Plot Analysis of Dominant Bacterial Orders The ternary plot of the dominant orders of microbial organisms also demonstrated a distinct distribution pattern of bacterial orders across the land management systems. Here, we found a strong association of Burkholderiales with unmanaged areas. It was the most dominant order in unmanaged soil. Other abundant orders were Sphingomonadales and Sphingobacteriales. Meanwhile, association of Vicinamibacterales was higher with both lavender cultivation system and Wheat based rotation. On the other hand, with wheat based rotation we found relatively higher abundance of Vicinamibacterales, Burkholderiales and Chitinophagales. The distribution of some orders around the centroid also indicates balanced distribution of some microbes across all the land management systems. Bacterial Community Diversity Indices across land management Alpha Diversity Indices The Alpha diversity analysis was conducted to study the microbial community structure through the richness and the evenness of bacterial communities under soil subjected to differing land management system. Microbial community richness was estimated using Chao1 index. Here, the higher index indicated higher microbial richness and abundancy of species. The highest chao1 index was in Wheat based rotation (1928.703) followed by lavender cultivation (1917.316). The lowest chao1 index was observed in unmanaged area (1427). In line with this we also found higher observed features in Wheat based rotation and Lavender cultivation (1915 and 1907 respectively). Among diversity indices, Shannon index that accounts for richness and evenness of the microbial organisms, exhibited higher values for Lavender Cultivation (9.806) and Wheat based rotation (9.676) with relatively lower index in unmanaged soil at 8.675. Hence higher diversity was observed in Lavender and wheat based rotation. On the other hand, low dominance in both lavender cultivation (0.002) and wheat base rotation (0.003) indicates there was very low dominance of any single taxon in these soils, which was in contrast to the dominance value of 0.008 in unmanaged soil. Meanwhile, Simpson index indicated a higher diversity across all land management with 0.998 in Lavender, 0.997 in wheat based rotation and 0.992 in unmanaged soil with relatively higher diversity in managed soils. Pielou’s Evenness also reflected the evenness of species abundance in Lavender cultivation and Wheat based rotation with relatively lower Pielou’s evenness. This leads to an understanding of how management and fertilization regime helps increase the microbial richness in soil. Whereas, the higher dominance and low Simpson values are an indication of microbial community dominated by fewer taxa in unmanaged soil. Beta Diversity Indices The Beta Diversity indices were calculated with both weighted UniFrac and Unweighted UniFrac distance metrics that analysed the dissimilarities between different land management systems. Weighted UniFrac is based on the phylogeny and abundance based method whereas Unweighted UniFrac is based on the presence and absence based method. We found higher dissimilarity observation with unweighted UniFrac distance matrix compared to Weighted UniFrac distance matrix. For instance, we found highest dissimilarity between the unmanaged soil and Lavender cultivation with Weighted UniFrac distance of 0.427 and Unweighted UniFrac of 0.580, indicating substantial differences in both community composition and abundance structure. We also found higher dissimilarity between unmanaged soil and wheat based rotation with UniFrac distance of 0.362 (weighted) and 0.520 (unweighted). However in case of Lavender cultivation and Wheat based rotation, we found relatively lower degree of dissimilarity with 0.267 (Weighted) and 0.536 (Unweighted). This may suggest a partial overlap or similarity in community structure between managed soil with nutrient availability, tillage, plantation and enriched taxa with plant root influence. Principal Coordinates Analysis (PCoA) Principal Coordinates Analysis (PCoA) helps in understanding the differences in microbial community composition with both Weighted and Unwieghted UniFrac distances. In Weighted UniFrac distance, the first principal coordinate (PC1) explained 75.09% of the total variance and PC2 explained 24.91% of the variance. This is crucial because there is a distinct separation of the effect of land management on the microbial communities. The Weighted UniFrac plot that also accounts for relative abundance, showed clear distinction between the land management systems with distinct microbial communities. PC1 (56.65%) and PC2 (43.35%) together explained the entire variation, suggesting strong influence of both species composition and abundance on microbial community structure. Soil Microbial Function Prediction of Soil Bacterial Communities FAPROTAX-based functional profiling are significant in analysing and predicting the differences in microbial function of the microbial taxa in a community. We found that in unmanaged area, functions associated with aromatic compound degradation, such as chitinolysis, ureolysis, cellulolysis etc. were enriched. This was relatively less in Lavender and markedly reduced in wheat based rotation. This also indicates that the soil under unmanaged area with native taxa may dominate and have biodegradative potential. On the other hand, in cultivated areas, functions associated with photosynthesis such that of photoautotrophy, oxygenic phototautotrophy which may be linked with root associated energy metabolism. In wheat based rotation we found that the functions associated with Nitrogen cycling such as nitrogen reduction, nitrification, nitrogen and nitrate respiration were present. This in an indication of the nitrogen transformation process with roles of microbes in Nitrogen cycling. Furthermore, functions associated with pathogen and symbionts were higher in unmanaged area indicating the suppression or absence of those microbial taxa in managed areas. Taxonomic Abundance Cluster heat Map of soil Bacterial Community The heat map of most abundant 35 phyla showed significant changes in microbial community due to the influence of land management system. In unmanaged area, we found that Proteobacteria (54.75%) dominated the microbial community that was followed by Bacteroidata and Acidobacteria. However, in lavender cultivation we found Actinobacteriota as the dominant class with 34.20% abundance, which was followed by lower (20.56%) Proteobacteria and Acidobacteriota (20.11%). The highest proportion of Chloroflexi (11.61%) and Gemmatimonadota (5.21%) was also observed in Lavender cultivated soil as well. On the other hand, with wheat based observation, Acidobacteriota (28.73%), Actinobacteriota (19.97%) and Proteobacteria (17.50%) made up sort of balanced distribution of microbial phyla due to its influence. We found that Wheat based rotation formed a distinct cluster, indicating a unique microbial community, enriched in phyla such as Abditibacteriota, Planctomycetota, Verrucomicrobiota, Acidobacteriota, and WS2. Lavender cultivation exhibited high abundance of Myxococcota, Thermoplasmatota, and Actinobacteriota, with lower levels of Proteobacteria and Bacteroidota compared to unmanaged soil. Unmanaged soil however showed strong representation of Proteobacteria, Bacteroidota, and Bdellovibrionota, while exhibiting reduced levels of Firmicutes and Myxococcota. Hierarchical clustering grouped Lavender cultivation system and unmanaged soil microbial community closer together, while wheat based rotation stood out as compositionally distinct. At species level, a general diversified pattern was observed with slightly higher diversity under Lavender cultivation. Since the relative abundance of the top 10 species comprised a low percentage, ‘others’ occupied 98.18% in Lavender, followed by unmanaged land (96.53%) and wheat-based rotation (95.98%). For instance, Nitrospira japonica and Gemmatimonadetes bacterium showed an increase in relative abundance under Lavender. A higher percentage of Lysobacter sp. , Adhaeribacter terrae , Caenimonas sp . and Solitalea koreensis in uncultivated areas was observed. Nitrospira japonica and Actinobacterium WWH12 were higher in cultivated areas. Phylogenetic tree of Soil Bacterial Community A phylogenetic tree of 100 most abundant genera was constructed to exhibit the evolutionary relationship of the microbial taxa in a community and its link with the genus present in the soil. We found that majority of the microbes present belonged to Proteobacteria, and Bacteroidata phyla. For instance, genera such as Massilia, Methylotenera, Pseudomonas, Sphingomonas which originated from Proteobacteria phylum were dominant in Uncultivated and unmanaged area. Likewise, we also found genus like Gemmatimonas, Candidatus Nitrososphaera etc evolving without following the typical evolutionary tree. Meanwhile, genera such as Rubrobacter (evolved from Phyla Actinobacteriota), Bacillus (evolved from Phyla Firmicutes), Nitrospira (evolved from Phyla Nitrospirota), Bryobacter (evolved from Acidobacteriota) were abundantly present in wheat based rotation. In case of Lavender cultivation we found that genera such as Gemmatimonas (Gemmatimonadota), MND1 and Sphingomonas (from Proteobacteria) were abundant. Along with that, here we observed a higher incidence of genus from phyla Actinobacteriota, as well as Proteobacteria with significant abundance of Gaiella, Agromyces, Mycobacterium, Streptomyces and Iamia. DISCUSSION The influence of soil management system on Soil Parameters Agricultural land management practices have a significant effect on the physicochemical and biological parameters of the soil. In our study, we found that Land management practices have a significant impact (p < 0.05) on the pH and the EC of the soil (Table 3). The slightly lower pH observed under an unmanaged area with perennial wild grasses and tree cover can be attributed to the type of organic matter, its decomposition and the leaching of positive ions in the soil. For instance, the continuous input of organic litter over the years can release H + ions into the soil solution, which increases the soil acidity (Hong et al., 2019 ). And since the quality of biomass differs in its decomposition rate, it also affects the release of ions and weak acids and can shift the soil acidity. However, even though the difference in pH was significant in our study, pH across the sampling sites was neutral to alkaline. Soil pH is affected by anthropogenic factors, environmental factors, and biomass type, which varies with slight changes in scenario (Hong et al., 2019 ; Fabian et al., 2014 ). Our finding of slightly lower pH in unmanaged areas with perennial cover is in line with Fabian et al. ( 2014 ), who reported that soil under perennial grass cover has lower pH than cultivated soil with regular tillage. The parent material and the soil type play a crucial role in the regulation of soil pH (Fabian et al., 2014 ). Hence, multiple studies under different temperature and biomass variations would help assess the impact of these factors on physiochemical parameters. Both lavender cultivation and wheat-based systems maintained higher, more neutral-to-alkaline soil pH, likely due to management practices such as liming, fertilization, or organic matter addition. The uncultivated area tended to have lower pH, reflecting natural leaching, absence of amendments, and heterogeneity in vegetation and soil processes. This suggests that agricultural management stabilizes soil chemical properties, which can be beneficial for plant growth and microbial functioning. Our finding of higher pH aligns with the findings of Cai et al. ( 2019 ), which indicated higher yield and increase in pH with manure application compared to fertilizer. Soil pH can serve as an indicator of microbial regulation since its influence on soil microbial diversity has been reported extensively (Malik et al., 2018 ; Tripathi et al., 2018 ). It may result in stochastic clustering of bacterial communities or a much deterministic clustering based on the soil pH, although the actual mechanism is not clear (Tripathi et al., 2018 ). Hence, regulation of soil pH or drastic shift to extreme pH, particularly due to anthropogenic activity, could provide insights into the practices and their role in microbial community functioning along with microbial characterization. The monitoring of long-term pH under unmanaged and managed land might study acidification and alkalinity. Land use strongly influences soil salinity, as reflected by EC values (Table 3). EC is the measure of the concentration of ions in soil. Overall, our findings were that across all land management, the soil was non-saline (0 < 2 dS/m). However, the Lavender cultivation system showed significantly higher soil salinity compared to the other two land management, which might be due to its perennial nature, potential build-up of ions from reduced leaching, or specific soil amendments. The amendments of compost and manure addition provide a higher negatively charged surface for positive salt ions (Cooper et al., 2020 ). Since lavender cultivation is associated with higher EC, monitoring for potential long-term salinity effects may be needed. Both the uncultivated grassland and wheat-based systems maintained lower EC levels, indicating minimal salinization risk under these land uses. The lower EC in wheat-based rotation, despite fertilization, might have resulted from greater nutrient removal through harvesting or seasonal leaching. The higher EC may be a result of the addition of organic manure and compost (in Lavender) and the presence of organic matter in unmanaged plots. The increased adsorption area of soil humus complexes increases the cation exchange capacity, which subsequently affects the EC (Husson et al., 2018 ). Uncultivated and wheat-rotation systems support lower and more stable EC levels, contributing to more favourable conditions for soil microbial activity and plant growth. Moreover, soil type characteristics such as soil type and structure also play a significant role in the moisture evaporation in soil (An et al., 2018 ). Our study does not have the resources to discuss this aspect. However, this increase in evaporation is possible as there was no provision for mulching in Lavender. Along with this, the addition of manure and compost regularly increases the CEC of the soil, which in turn could increase the soil EC. This is reflected by comparatively lower moisture in Lavender cultivation, and we believe it could have played some role in relatively higher EC in the soil. On the other hand, although rich in organic matter, the accumulation of litter in unmanaged land also acted as an organic mulch, preventing moisture loss and could have regulated the EC more effectively. This could be the differentiator in the differences of EC between these two land management types. For instance, Husson et al. ( 2018 ) also documented a positive relationship between EC and soil texture, organic matter and CEC of the soil. This is also similar to our findings of higher EC in lavender cultivation and unmanaged areas. Year-round fertilization and removal of residue after every crop cycle have shown a significant impact on both the pH and EC of the soil. This is in comparison to unmanaged land with wild growth, where the litter enters the soil as a source of organic matter every year. Hence, in the case of Lavender residue, quality might have played a significant role in the soil. Wheat cultivation and unmanaged areas with grass support stable, low-salinity soils with slightly alkaline pH are beneficial for microbial and plant health. In contrast, the Lavender system, while still within neutral pH, shows signs of higher salinity, which may affect soil biological activity and long-term sustainability. These findings emphasize the positive impact of low-input and perennial systems on maintaining soil chemical balance. Soil respiration and its relationship with moisture content across agricultural system Our study found that differing land management have significant influence on the soil respiration and the gravimetric water content. The higher moisture content in the unmanaged soil might be due to the accumulation of plant residue of the wild grasses and leaves that functioned as a mulch layer ( Error! Reference source not found. ). Soil respiration is a representative indicator of soil microbial activity and organic matter mineralization (Vanhala et al., 2005 ). Previous studies have indicated that the water holding capacity of soil rich in organic matter increases in comparison to soil that lacks organic matter (Djigal et al., 2012 ). Besides the organic layer, organic matter prevents the evapotranspiration loss of soil, increases moisture retention, reduces runoff, and influences the microbial functioning in soil (Fang et al., 2007 ; Coppens et al., 2006 ). Moreover, it is also likely that the soil was under no tillage regime that increased its moisture content. Tillage is linked with disruption of soil structure, exposure of soil micro and macro pores and loss of soil moisture with no protective organic mulch. However, the relationship of the tillage system and the porosity of soil is directed by the soil texture, and under no-tillage areas, the retention of soil moisture is higher (Feiziene et al., 2018 ). The results on CO2 evolution due to management changes have not been uniform, with differing site-specific results (Feiziene et al., 2018 ; Franzluebbers et al., 1995 ). In our case, however, we observed higher CO2 evolution with perennial grass cover and shrubs under unmanaged areas. The presence of high lignin organic residue has lower carbon use efficiency and may result in higher soil respiration (Almagro et al., 2021 ). It is also possible that the root structure of wild grasses and shrubs below 2mm might have influenced CO2 production, which was different from the lower amount in other land management. The role of diversity in increasing soil respiration has also been documented (Madritch & Hunter, 2003 ). Apart from this, the metabolic quotient (qCO2), the ratio of respiration to microbial biomass, might have shed some more light on understanding the greater energy use efficiency of the microbe or indicate the growth habit of the microbial community (Maeder et al., 2002). For instance, the presence of grasses and deciduous plants will result in a higher decomposition rate and less stabilization of recalcitrant organic matter, which increases CO2 production in soil (Howard & Howard, 1993 ). Hence, the utilization of mature compost and manure applications, such as our lavender cultivation system, may be help moderate carbon stabilization while stimulating microbial growth in the soil. Besides, a record of decrease in soil respiration may happen in the case of compost-amended soils as time passes due to a decrease in SOC and labile carbon fraction (Kowaljow et al., 2010 ). The relationship between soil respiration and gravimetric water content was high (R2 = 0.45, p > 0.05); however, it was not statistically significant (Fig. 6). This indicates a positive relationship between soil respiration rate and soil moisture, with a positive influence of soil moisture on the soil respiration rate. Our results are similar to the findings by Howard and Howard ( 1993 ) and Gerenyu et al. ( 2005 ), who reported that an increase in soil moisture up to an optimal point increases the CO2 evolution rate in a wide range of soils. However, soil respiration is largely influenced by soil temperature, and the organic matter of the soil and changes in this dynamic complex bring variation in the evolution rate (Ren et al., 2017 ; Franzluebbers et al., 1995 ). The presence of readily degradable and degradation-resistant compounds also impacts the soil microbial functioning. Hence, further studies on the components involved will provide a much clearer and more comprehensive understanding. Although with an increase in CO2 in uncultivated areas, higher enzyme activity would be expected; however, balanced mineral fertilization with rotation (in wheat) and application of compost and manure (in Lavender) showcased higher enzymatic activity and carbon stabilization from an initial perspective. However, further studies are necessary to understand the long-term impact on soil biology. Enzymatic activities across different agricultural system Soil enzyme activities are a strong indicator of decomposition and microbial and soil biological health in that they reflect the biochemical reaction in the soil (Sinsabaugh et al., 2008). Our results indicate that land management significantly affects the enzymatic activity in the soil (Table 4). We found significantly higher Dehydrogenase and β-Glucosidase activity under Lavender cultivation with the application of mature manure and compost. Organic amendments with manure and compost often lead to positive effects on soil physical properties, nutrient availability and biology (Marschner et al., 2003 ). These findings are similar to the findings of elevated enzymatic activity after the application of farm yard manure, organic amendments and balanced NPK application by Hu et al. (2014) and Marschner et al. ( 2003 ). However, the enzymatic activity is affected by the decomposition rate and the quality of aboveground and lower-ground biomass. The lower enzymatic activity observed in unmanaged areas with wild growth can be attributed to the heterogeneity of the litter present, which may have a slow decomposition rate, which is reflected in the enzymatic activity. For instance, C: N ratio of the residue influences the enzyme production and activity. The lower C: N ratio in agricultural soil may increase the enzymatic activity (Zhang et al., 2018 ). Besides the influence of litter C: N ratio in enzymatic activity, the quality of organic matter and crop type also have the ability to shape the microbial community (Wagner et al., 2016 ). Areas rich in initial fresh litter that are easily degradable may lead to higher enzymatic activity and assemblance of wider microbial groups, while areas rich in recalcitrant litter with wider C: N ratio can lead to assemblance of narrow microbial groups that can decompose and shape the microbial community (Bai et al., 2024 ; Marschner et al., 2002). The assessment of Dehydrogenase and β-glucosidase is crucial in carbon cycling since this enzyme of two different classes are involved in the oxidative and hydrolytic breakdown of complex compounds. Furthermore, the availability of nutrients and the easily degradable compounds in compost in the case of Lavender cultivation could have increased enzymatic production. The significantly high enzymatic activity in Wheat-based rotation might be due to the availability of easily available mineral nutrients to microbial communities. This leads to the easy proliferation of microbial populations, which is reflected in soil enzymatic activity. Likewise, the addition of residue and year-round application of compost and manure leads to elevated enzymatic activity. The Nitrogen availability is considered a driver of enzymatic activity, with an excess amount of Nitrogen available for plant and microbial growth (Curtright & Tiemann, 2021 ). The enzymatic activity is also influenced by the C: N ratio of the residue in the soil. The rate of decomposition varies with the carbon to lignin content. The increase in recalcitrant compounds, which also includes later stages of decomposition, and N-poor litter may increase CO2 evolution, leading to low microbial carbon use efficiency. Likewise, it can also reduce the enzymatic activity of beta-glucosidase, Urease, and Phosphatase (Almagro et al., 2021 ). Meanwhile, mineral fertilizer is linked to a higher number of microbes, which also had the same effect on the diversity (Table 9). Dehydrogenase is one of the few enzymes that are intracellular and present in viable cells and indicate microbial enzyme production (Dick & Kandeler, 2005 ). Besides this, the availability of biomass is a determinant factor in the rate of decomposition of residue, which is again reflected in the soil enzymatic activity. The Nitrogen availability in the soil through mineral fertilizer and residue mixing (in Wheat based rotation) or compost and manure (in Lavender) could have increased the enzymatic activities in comparison to the unmanaged area (Almagro et al., 2021 ). For instance, Kemp et al. ( 2003 ) also found that the rate of decomposition of above-ground biomass, such as leaves is significantly faster in comparison to the below ground root litter. It indicates the role of the rooting system growth and structure and the presence of leaf litter in microbial utilization, which is reflected in the microbial respiration in soil. Although the moisture content was higher, which we believe is due to the organic litter of perennial grasses and deciduous shrubs, due to the high diversity of above-ground biomass and low amount of simple carbon compounds in comparison to areas with manure and compost (Lavender Cultivation) and mineral fertilization, we found higher enzymatic activities under cultivated areas in comparison to unmanaged area. However, this diversity in the composition of litter also would be clear with the microbial community assessment. On the other hand, it is also possible that the heterogeneity of substrate that varies in its C: N stoichiometry may sustain the diverse microbial populations in smaller numbers, whereas the availability of nutrients under Lavender and wheat rotation areas may support larger proliferation and a number of narrow saprotrophic organisms. Another explanation could be that the organic matter decomposition takes place in phases where high-quality litter (with low C: N) decomposes quickly, releasing nutrients and increasing extracellular enzymatic activity, which is followed by the decomposition of low quality litter (high C: N, Lignin: N) (Liu et al., 2023 ). This causes a shift in the number and abundance of microbial organisms in the community. Colonies growth on media across different agricultural system We cultured soil microbes in a number of different universal fungal, bacterial growth media, and specialized microbe growth media (Fig. 5). After 2 to 3 serial dilutions, we have presented the growth at a uniform dilution rate for all land management (Table 6). This conventional approach to studying the growth of microbes present in differing soil under enabling conditions, relies on morphological identification and is not representative due to numerous biases and hence is not reliable. Regardless, we continued with it to observe the growth and morphological growth of selective and general-purpose media. A higher number of Actinomycetes was observed in Wheat based rotation and lavender, which indicates that the plant type has a significant effect on growth. The microbial population adapted to heterogenous (such as that of unmanaged land) may show some selective effect when cultivated on selective media (Vieira & Nahas, 2005 ). Hence, we observed a lower number of CFUs in unmanaged areas with organic litter, which might have been sustaining k strategists which did not proliferate in nutrient-rich media. The effect of chemical fertilization was visible in our colony growth study. Generally, a higher number of colony growth was observed in the Wheat-based rotation, which is likely due to the adaptive ability of the saprotrophic population. The selective and general purpose media are rich in nutrients that allow easy proliferation of r strategists. Belay et al. ( 2002 ) also found a higher bacterial population under nitrogen fertilization. In addition, the colony's growth is influenced by temperature and media, which has influenced the growth of microorganisms (Viera & Nahas, 2005). In long-term fertilization, especially with Nitrogen and Fertilizer availability, the CFU growth of the bacterial population in artificial media is higher, which could have been through the survival of microbes that has a better mechanism of nutrient utilization. Moreover, this may also lead to a less diverse microbial growth at a higher number (He et al., 2008 ). Metagenomic Characterization across agricultural system Our findings suggest that land management practices influence the genetic composition of the microbial community in soil, allowing the proliferation and dominance of distinct microbial taxa. This may be through selection pressure or conducting conditions (Wang et al., 2020 ). As a result, our observations of varied microbial taxa in cultivated soil (lavender cultivation and wheat-based rotation) suggest that regular and additive nutrient supply, along with multiple other factors, contributes to increased bacterial diversity in the soil. Meanwhile, decreased diversity in unmanaged soils indicated the survival of fewer and less diverse microbes with distinct life strategies (Osborn et al., 2024; Chen et al., 2021 ). The differences in GC (S1; Table 5) may indicate a reflection of the GC-rich genome between the land management systems. For instance, the presence of phyla such as Actinobacteria in abundance may be present in long-term or perennial cropping systems (Delgado-Baquerizo et al., 2018 ). Likewise, we observed a high total base count, which could mean a diverse microbial community in wheat-based rotation that may be metabolically diverse. Nonetheless, we found a higher total base count across the three land management systems, which shows that the microbial community between these systems have comparable community structures. The higher base number in both lavender and wheat-based systems is likely due to the presence of plant community under a fertilization regime that increases the microbial richness and functional potential with additive benefits associated with rhizodeposition (Xiao et al., 2022 ; Berendsen et al., 2012 ). Overall, our study found a pronounced shift in the microbial community that is primarily mediated through management practices. For instance, under lavender cultivation, a perennial crop harboured a high population of Actinobacteriota and Acidobacteriota. This was expected as the land had been amended with compost and manure as well as since organic matter addition has been associated with a higher population of Actinobacteria, Firmicutes, Chloroflexi and other enzymatic activities (Wang et al., 2020 ). Our findings in Lavender cultivation with organic amendments are in line with this finding as well. In contrast, unmanaged soil, which contained a collection of wild grasses and leaves, harboured a remarkedly low Actinobacteriota population in this case. Here, taxonomic assessment of phyla revealed that the Proteobacteria phylum dominated the microbial community in abundance (Fig. 8). However, under this phyla, between Alphaproteobacteria and Gammaproteobacteria, the latter (40.94%) dominated in unmanaged soil. These Alphaproteobacteria are known to be involved in organic matter decomposition, and they are abundant in forest soil (Kim et al., 2021 ). In the two cultivated soils, Proteobacteria did not overwhelmingly dominate, and both Alphaproteobacteria and Gammaproteobacteria were evenly distributed farther down the taxonomy. It further strengthens the argument that regular organic amendments help maintain a larger and more diversified microbial community positively associated with carbon cycling. The increasing abundance of orders like Vicinamibacterales and Gaiellales indicates the preferential colonization and proliferation in nutrient-rich areas. These orders were common in Lavender cultivation and wheat-based rotation but were lower in unmanaged land. These findings demonstrate the strong influence of plant species on the rhizosphere and bulk microbial community composition at the order level, with the land management system influencing the distribution of bacteria and supporting a distinct subset of bacterial taxa. The higher relative abundance of ‘others’ among genera-based assessment in Wheat based rotation (more than 82%) and Lavender cultivation (more than 85%), in contrast to the unmanaged soil, with others occupying over 57%, indicates that the managed soils have highly diverse and complex microbial structure. Here, as evidenced by Alpha diversity, the diversity indices are extensively higher in soil with regular application of organic and mineral fertilization. The observed features across the three land and their similarity and dissimilarity also explain that planting biomass and no-tillage and the addition of organic matter enhances microbial diversity. Likewise, crop rotation and nutrient availability are positively linked to higher OTUs in soil. This was reflected in the low similarity of OTUs observed in unmanaged sites to that of both cultivated soils. In the case of organic amendments, organic carbon in compost-amended soils shows a pronounced effect on the microbial biomass and the microbial community. Saprophytic organisms are dependent on organic carbon-rich compounds for their growth and metabolism (Lupwayi et al., 2017 ). This is similar to our findings of a higher abundance of Actinobacteriota (34.2%) in Lavender cultivation. Here, compost and manure were added regularly, resulting in a much more diverse microbial community, which is in contrast to the lower proportion of Actinobacteriota and Acidobacteriota in unmanaged soil. This was similar in both of the cultivated soils where Actinobacteriota and Acidobacteriota, primarily involved in decomposition, were abundant. Acidobacteria are associated with resilience to acidic conditions (Philippot et al., 2013 ) Similarly, the heat map further indicated the association between the land management systems and the microbial taxa. Here, what showcases the complex action and mechanism associated with cultivated areas are the ecological niches that harbour much higher bacterial phyla numbers than unmanaged soil. Among the top 30 abundant genera, these genera comprise 54.74% of the total observed genus in unmanaged soil. In contrast, the most abundant 30 genera only comprise 22.68% (Lavender cultivation) and (slightly higher) 29.98% in Wheat based rotation. One other aspect in litter rich areas is concerned with its role in reducing nitrogen availability. Losses through NO3 − leaching, gaseous release of N2 is linked with quality and amount of litter presence (Martínez-García et al., 2021 ; Lyu et al., 2019 ). Higher N cycle-related metabolism, including nitrite respiration, nitrate, and nitrite ammonification, was likewise linked to our function potential prediction in unmanaged soil (Fig. 17). This also demonstrates the effect that soil management and litter have on the nitrogen cycling process. A generally higher presence of genera from Phyla Proteobacteria and Bacteroidata was observed from the phylogenetic tree (Fig. 19). However, we found higher diversity across all land management systems at the species level. There was a higher abundance of Lysobacter sp. , Adhaeribacter terrae , Caenimonas sp ., and Solitalea koreensis in uncultivated areas. Strains of Lysobacter are known to have pathogen suppression and extracellular enzyme production, with Caenimonas reported in unamended soils and present under stress (Rodríguez-Berbel et al., 2020 ; Gomez Expósito et al., 2015). Meanwhile, species like Nitrospira japonica , Gemmatimonadetes, and Actinobacterium (WWH12) were higher in cultivated areas. Gemmatimonadetes are associated with anoxygenic photosynthesis, which has been reported in terrestrial and aquatic systems (Mujakić et al., 2022 ). Species from Actinobacteria are significant due to their role in carbon cycling, extracellular hydrolytic enzyme production, and organic matter degradation (Zhang et al., 2019 ). Nitrospira is associated with the Nitrite-oxidizing mechanism and is a key factor in nitrogen cycling (Daims et al., 2015 ). Gemmatimonadetes may also have slow growth and be helpful in long-term stability (Zeng et al., 2015). These are reported to be ubiquitous, with positive roles in vegetation restoration, disturbed soils, and areas rich in nutrients. Their slower growth rate indicates a link to their resilience to stress and play a stable role as k-strategists (Mujakić et al., 2022 ). The root structure, its significant role in carbon exudation, and the growth cycle in wheat-based rotation and lavender may also have been involved in the microbiome shift compared to unmanaged soil. Hence, mixed cropping is crucial to bacterial and fungal biomass due to its role in prompting enzymatic activity through exudation. Although plant species solely are not highly influential in microbial communities since they may not change the proportion of dominant taxa but may increase the relative proportion of rare species (Zhang et al., 2025 ). This also sheds light on the dynamic complexities of the microbial community and the influence of multiple factors. Apart from that, the dominance of Gammaproteobacteria and Bacteroides has been associated with fresh litter presence and its decomposition, which has a positive role in carbon mineralization (Fierer et al., 2007 ). Based on our observation, the higher labile organic matter and grass root exudates can help proliferate but result in lower taxa distribution under nutrient-limited conditions. Microbial community and Diversity and its structuring based on differing Management systems The alpha diversity analysis revealed clear differences in bacterial community structure under differing land management practices between rhizosphere-associated cultivated soils and unmanaged land. The Lavender cultivation and wheat-based rotation exhibited significantly higher species richness and diversity than the unmanaged area, which is reflected by the Chao1, observed features, Shannon, and Simpson indices. The increased Chao1 richness in both cultivated soils is likely due to the root-associated environments that provide a conducing and broader range of ecological niches and substrates, supporting a more diverse microbial community. This is also aided by the regular application of nutrients through organic amendments and mineral fertilizers. Root exudates, composed of sugars, amino acids, organic acids, and secondary metabolites, stimulate microbial proliferation and recruitment (Berendsen et al., 2012 ; Bulgarelli et al., 2013 ). The notably higher richness in the wheat and lavender rhizospheres compared to bulk soil aligns with previous findings that plant roots serve as microbial hotspots in the soil matrix (Mendes et al., 2013 ). However, the influence of the rhizosphere effect may be reduced depending on the site-specific and biomass in the environment. Based on alpha diversity indices, we found that management practices in Lavender and wheat cultivation can promote higher bacterial richness, diversity, and evenness in the soil microbial community. These results indicate that plant presence and identity modulate not only microbial community composition but also their ecological functional potential, with implications for nutrient cycling, soil health, and bioremediation. Our findings of higher Xanthomonadales in unmanaged areas indicate the abundance of decomposers due to their role in forest litter decomposition. These bacterial orders are also linked with the possible association with Nitrate mineralization in soil (Kim et al., 2019). Sul et al. (2019) found that bacterial richness is higher in managed agricultural land than in unmanaged plots with grass. In some amendments, like charcoal, the management practices have an edge over the influence of the microbial community (Hardy et al., 2019 ). The involvement of management practices creates a difference in cultivated land where limiting nutrients are addressed with multiple other practices. This contrasting difference exhibits the scenario between cultivated and unmanaged soil. The FAPROTAX analysis also provided insights into the status of uncultivated soil. The functions associated with hydrocarbon and aromatic compound degradation were substantially present. They may also explain the dominance of native soil taxa adapted to degrading organic residue and organic compounds in soil. Similarly, Phylum Firmicutes and genus Bacillus were highly abundant in Wheat based rotation. It could be the role of higher nutrient availability and its beneficial effect in cultivated soils. For instance, we also observed the genus Nitrospira in Wheat based rotation, which is associated with a positive role in Nitrite oxidation and hence plays a substantive role in Nitrogen cycling (Gu et al., 2017 ; Fierer et al., 2007 ). The functional potential indicated that the microbial functioning related to Nitrate reduction and denitrification were higher in Wheat based rotation. We found that Taxa such as Chitinophagales and Pyrinomonadales were abundant under the conducive environment of Wheat-based rotation and are involved in the breakdown of complex compounds such as chitin (Chen et al., 2022 ) and aid in carbon mineralization. Hence, these taxa were present in unmanaged areas, which explains its role in litter decomposition. Moreover, the availability of Nitrogen is another driving factor in shaping bacterial communities. Excessive fertilization is reported to have a negative effect on the bacterial community (Chen et al., 2022 ). Hence, monitoring the reflection of management on microbial diversity, in the long run, will be crucial to improve microbial health. The Chao1 index reflected the wider niche provided by the cropping system, the plant biomass and nutrient availability that can support a diverse microbial community. Contrastingly, unmanaged areas exhibited lower diversity and higher dominance, suggesting fewer competitive or specialized taxa without rhizosphere influences. Based on our observation, a crucial aspect is the biomass density, the type of biomass. A number of studies have indicated that undisturbed ecosystems may entertain a distinctly differing microbial community (Buresova et al., 2021 ; Kim et al., 2021 ) that is driven by physiochemical parameters, amount and type of litter. In our case, we had wild growth but sparse, but still, we observed differences in Chloroflexim, Firmicutes, and Gemmatimonadota (higher proportional abundance in cultivated areas) between the differing management systems. The beta diversity analysis revealed clear shifts in microbial community composition between the differing land management systems. We found higher UniFrac distances, which explained the dissimilarity between lavender cultivation and Wheat-based rotation in uncultivated soil. This reflects the strong influence of root exudates in shaping distinct microbial communities, consistent with previous findings (Berendsen et al., 2012 ; Bulgarelli et al., 2013 ). However, we also found a lower dissimilarity between lavender cultivation and Wheat-based rotation, which suggests a certain overlap in observed taxa, likely reflecting shared functional groups involved in nutrient cycling or root colonization. These results support the concept that plant species act as key drivers of rhizosphere microbiome differentiation, impacting community structure and phylogenetic diversity. Regarding disease incidence, we found that taxa like Gaiella and Bacillus in cultivated soil, which is promising. These genera have been associated with areas of low disease incidence, indicating their positive metabolism in pathogen suppression (Babinska-Wensierska et al., 2024 ). More likely, we found a high amount of Thermoleophilia (16.48%) in a lavender field. Hence, their distribution has played a positive role since the relative incidence in unmanaged soil is lower. Beneficial genera like Bacillus are widely used as PGPR-promoting organisms, biofertilizers that promote nutrient availability through metabolite production and also suppress diseases through antagonism (Babinska-Wensierska et al., 2024 ; Saxena et al., 2020 ). Actinobacteria and Firmicutes are involved in the breakdown of recalcitrant and complex organic compounds, which were present and in line with their increased abundance in Wheat based rotation and Lavender cultivation (Verzeaux et al., 2016 ). The presence of biomass, the ecological niche for microbe proliferation and the addition of manure and fertilizer can increase the diversity of decomposers. Wang et al. ( 2020 ) also found that long-term crops provide resources for supporting the proliferation of Actinobacteria and Firmicutes. One crucial aspect is the higher abundance of Acidobacteria in both Wheat based rotation and Lavender cultivation. These phyla are considered k strategists that exhibit slower growth rate and do not proliferate rapidly with substrate availability (Philippot et al., 2010 ). Hence, it might be one reason for the lower contribution to basal respiration in cultivated soil and higher CO2 production in uncultivated soil (Fig. 6). Besides, Acidobacteria occupied lower abundance in uncultivated soil, and instead, we observed a higher proportion of Proteobacteria and Bacteroidetes, which are r-strategists with lower substrate use efficiency. Moreover, the dominance of Gammaproteobacteria under Proteobacteria in uncultivated areas indicates the relationship with substrate litter since these are primary decomposers (Buresova et al., 2021 ; Fierer et al., 2007 ). Vicinamibacteria are oligotrophs involved in the solubilization of inorganic phosphorus through enzyme production that mediates P mineralization and have shown stress resilience (Boutsika et al., 2024). We found a high relative abundance of this class belonging to Acidobacteroita in lavender cultivation and Wheat based rotation, showing that the planting system had the positive benefit of allowing higher proliferation. This proliferation of bacterial groups and Phosphorus availability is mediated by gcd genes that, through multiple pathways, increase its availability under disturbed soil (Liang et al., 2020 ). This signifies that these bacteria increase under nutrient amendments as well. Since, studies have shown differing results in the increase and decrease of copiotrophic organism after fertilization (Dai et al., 2020 ). Therefore, the role of the dynamic interaction with cropping patterns and planting systems could help maintain the diverse structure of bacterial communities. Bacteroidia, Gammaproteobacteria dominance makes up over 57% of the dominance in unmanaged soil. These are r-strategists linked with higher growth and utilization of polysaccharides and complex compounds, which relates positively to the presence of organic matter in unmanaged soils. However, it also elucidates the high fluctuation in the dominance of microbial groups. Surprisingly, we found that with nutrient supply, we found a balance between r strategists and k strategists, indicating the role of plants in mediating a balance of diverse bacterial communities. The alphaproteobacteria, Vicinamibacteria, and Actinobacteria, are oligotrophs that could lead to a microbial stability and resilient community that grows moderately with a positive role in nutrient cycling and is less sensitive to biotic and abiotic stress in the soil. The higher relative abundance of Acidobacteria in Lavender (20.11%) and wheat-based rotation (28.73%) and lower in uncultivated soil (12.96%) is also likely due to the substrate availability and substrate utilization ability of Oligotrophs. The higher presence indicates their ability to sustain microbial diversity since these thrive under low nutrient availability and do not dominate the community when nutrient availability is high (Dai et al., 2020 ). The microbial breakdown of lower C: N ratio litter increases soil organic carbon and nitrogen content and also has a positive effect on the enzymatic activity (Xiao et al., 2024 ). The presence of bacterial genera like Bacillus and Pseudomonas was evident in Wheat based rotation. It may be linked to having a positive effect on pathogen suppression through pathways such as biofilm formation and root colonization. These genera are supposed to positively interact around the root interface and create a protective barrier to pathogen proliferation (Tao et al., 2020 ; Bais et al., 2004 ). However, since the agricultural environment is such a dynamic and complex system, monitoring the effect of land management and cropping on microbial community structure is required. The sensitive response to any changes in agricultural land management practices enhances their value in detecting and monitoring shifts in soil property dynamics from management. Our study demonstrates that agricultural management practices, along with the cropping system, can influence and shape the soil microbial diversity, alpha diversity, beta diversity and the functional potential of the microbial taxa present in the soil. The difference between Lavender and Wheat based rotation was also observed. Firstly, a highly diverse phylum classification in Wheat-based rotation might be due to the change in plant biomass with rotation that allowed for a diverse source of organic carbon-rich compounds. Besides this, the availability of nutrients. In this context, biomass is crucial since even diversification with wheat cultivars has been shown to shift microbial community structure in the rhizosphere with a higher abundance of Actinobacteria, Bacteroidetes and Proteobacteria in tall wheat cultivars (Kavamura et al., 2020 ). Sphingomonadales were higher in uncultivated areas and in Lavender Cultivation. We believe it is due to the association of these two land management practices with perennial presence, abundant complex compounds from biomass in uncultivated areas and compost in lavender cultivation. It has been reported that areas rich in the presence of recalcitrant litter and residue and areas with low nutrient availability have an association with the degradation of polycyclic aromatic hydrocarbons (PAHs) (Siddiqi et al., 2017 ; Jeys et al., 2002). Massilia, Pedobacter, and Pseudomonas are higher in unmanaged areas than both of the cultivated areas. Massilia are root colonizers and several species are involved in breakdown of chitin under nutrient stress (Faramarzi et al., 2009 ). Beneficial strains of Pseudomonas, and Bacillus are reported to produce IAA, and secondary metabolites (Chen et al., 2020 ). Hence, the clear demarcation and a distinction in the microbial diversity shows that unmanaged areas have microbial community structure dominated by limited taxa which may be explained by the selection pressure and stress continuation that allows for a dominance of limited taxa. Likewise, observations of beneficial bacteria involved in complex compound breakdown indicates their well-functioning mechanism however, probability of low substrate use efficiency poses question on their effect on carbon stabilization. On the other hand, soil management practices and cropping changes allow for a diversity microbial community structure with relative and proportionate distribution of r-strategists and k-strategists in agricultural soil. Hence, Sustainable management choices in soil amendment and cropping systems are crucial in balancing the soil microbial community structure. We believe long term monitoring managed and unmanaged land, their properties would provide a broader understanding of land management effect in soil. CONCLUSION Our study was conducted to understand the influence of 3 different land management practices on soil parameters and microbial community structure. We found that the management practices are a key driver of shift in microbial community composition with higher diversity in well managed and cultivated soil, primarily through fertilization and root mediated conducive environment. Alpha diversity and beta diversity indices indicated the distinct differentiation of the microbial distribution pattern in a microbial community. Higher enzymatic activities, moderate pH were observed in cultivated soils. Moreover, clear differentiation of highly diverse phyla and reduced phyla diversity were observed in managed and unmanaged soil respectively. This indicates the interactive influence of above ground and below ground biomass with fertilization regime that promotes higher diversity of microbial community. Meanwhile, unmanaged soil may promote lower diversity in microbial community that might be due to the aboveground biomass, decomposition processes, selective pressure which limits the proliferation of higher microbial diversity and exhibits presence of higher dominance of limited taxa. Therefore, understanding the influence of land use and management practices through identification and assessment of biological components/indicators are critical for evaluating the impact and effectiveness of land management strategies and agricultural practices early. Hence studying the long term influence on microbial community and enzyme activity with provide deeper insights into the applicability of management practices in agricultural soil. Statement and Declaration Authors Contribution Declarations Authors Contribution Karun Adhikari : Original Draft Preparation, Writing and Editing, Laboratory Analysis, Statistical analysis, Visualization Mariana Petkova : Writing -Editing Reviewing, Laboratory Analysis, Supervision Data Availability The sequencing data are available at NCBI Sequence Read Archive (SRA) under BioProject PRJNA1292883. Conflict of Interest The authors declare no conflict of interests. Funding The authors did not receive any funding for conducting the research. Karun Adhikari was supported by the Erasmus Mundus Joint Masters scholarship Program. References Allison SD, Vitousek PM (2005) Responses of extracellular enzymes to simple and complex nutrient inputs. 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system\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/d9bbc3ab1119c1d6be9e0dda.png"},{"id":92481430,"identity":"4dd6f95e-bf0e-4b88-aa74-5d1e339527f1","added_by":"auto","created_at":"2025-09-30 07:50:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":27001,"visible":true,"origin":"","legend":"\u003cp\u003eDehydrogenase activity under different Agricultural system\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/4b5530ac124adc2eab90d0af.png"},{"id":92482693,"identity":"fc52f9be-835c-4cb0-b0e2-5e24ad3043bf","added_by":"auto","created_at":"2025-09-30 07:58:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":26280,"visible":true,"origin":"","legend":"\u003cp\u003eBeta-Glucosidase activity under different Agricultural system\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/3b547fc5d3bf23e78ea9231b.png"},{"id":92481428,"identity":"458f62be-aceb-4339-8bd7-2a33b4730806","added_by":"auto","created_at":"2025-09-30 07:50:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":32856,"visible":true,"origin":"","legend":"\u003cp\u003eSoil Respiration Rate across three Agricultural System\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/26f7ee4f55f726dd8bbc510c.png"},{"id":92481438,"identity":"7544c7bc-4450-40de-9306-d505d9c7fc4f","added_by":"auto","created_at":"2025-09-30 07:50:51","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":66055,"visible":true,"origin":"","legend":"\u003cp\u003eInfluence of Land Management on Colony Forming Units across different Media\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/c6caf607e123e15bff0e9230.png"},{"id":92482695,"identity":"3c493467-450e-4094-ab35-56a6a02de297","added_by":"auto","created_at":"2025-09-30 07:58:51","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":57964,"visible":true,"origin":"","legend":"\u003cp\u003eGravimetric Water Content under the three Agricultural System\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/afc8b8053e1dbe576721bf9a.png"},{"id":92481437,"identity":"252d9833-7d53-402c-bae3-82b5f5f04f1a","added_by":"auto","created_at":"2025-09-30 07:50:51","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":36446,"visible":true,"origin":"","legend":"\u003cp\u003eLinear Relationship between Soil Moisture Content and CO2 evolution rate\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/a679f63ecdcaae03bde1c5df.png"},{"id":92481440,"identity":"99edf53d-048d-4329-94d5-0c7076243ca1","added_by":"auto","created_at":"2025-09-30 07:50:51","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":52613,"visible":true,"origin":"","legend":"\u003cp\u003eRelative Abundance of Microbial Phyla based on 16S region\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/c5d8a4b23aff028bb8547ac5.png"},{"id":92482698,"identity":"572eb70d-eab1-41f6-b3f0-fa8b5cc45bca","added_by":"auto","created_at":"2025-09-30 07:58:51","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":11341,"visible":true,"origin":"","legend":"\u003cp\u003eVenn and Flower diagram analysis of shared OTUs/ASVs across differing land management\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/e9803b417549abce77ea5009.png"},{"id":92482700,"identity":"5ef0abe0-3637-457b-bc28-3f5aac112420","added_by":"auto","created_at":"2025-09-30 07:58:51","extension":"jpeg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":109318,"visible":true,"origin":"","legend":"\u003cp\u003eTernary Plot depicting abundance of microbial abundance across land management\u003c/p\u003e","description":"","filename":"image12.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/34e2a6e214720330b02d79ed.jpeg"},{"id":92482706,"identity":"011a7aac-e50f-48ea-bc99-c6911955d066","added_by":"auto","created_at":"2025-09-30 07:58:52","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":58964,"visible":true,"origin":"","legend":"\u003cp\u003eAlpha Diversity Indices between the differing management System\u003c/p\u003e","description":"","filename":"image13.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/432fc004e1be9844d724f045.png"},{"id":92482712,"identity":"22ad32cf-869b-4a76-88c0-71b6742b16ab","added_by":"auto","created_at":"2025-09-30 07:58:52","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":83309,"visible":true,"origin":"","legend":"\u003cp\u003eBeta Diversity heat map with weighted Unifrac distance (above) and Unweighted Unifrac distance (below)\u003c/p\u003e","description":"","filename":"image14.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/708c0712856463ea5abe9f1c.png"},{"id":92481441,"identity":"8515fcae-ad20-4a84-9627-2343aa2a7b5f","added_by":"auto","created_at":"2025-09-30 07:50:51","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":27154,"visible":true,"origin":"","legend":"\u003cp\u003ePCoA based on Weighted UniFrac distance (left) and Unweighted UniFrac distance (right)\u003c/p\u003e","description":"","filename":"image15.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/4d794b6e0268809c8f97658f.png"},{"id":92482701,"identity":"80ea8507-a8de-4902-8d96-b66612237294","added_by":"auto","created_at":"2025-09-30 07:58:51","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":148903,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map of predicted microbial functions based on FAPROTAX analysis across three land management\u003c/p\u003e","description":"","filename":"image16.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/fc0352f0af7e911d65fa004c.png"},{"id":92481476,"identity":"5a0ba055-6427-4987-a859-724dce49b9c6","added_by":"auto","created_at":"2025-09-30 07:50:52","extension":"png","order_by":17,"title":"Figure 17","display":"","copyAsset":false,"role":"figure","size":221953,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map of Taxonomic Abundance at Class level across differing Land Management\u003c/p\u003e","description":"","filename":"image17.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/b5cf546a2e2d7d93a72dce81.png"},{"id":92483077,"identity":"b4bcec62-9c11-41d6-97ae-fce14b8881d9","added_by":"auto","created_at":"2025-09-30 08:06:52","extension":"png","order_by":18,"title":"Figure 18","display":"","copyAsset":false,"role":"figure","size":345253,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic Tree of Soil Bacterial Community at Phyla level\u003c/p\u003e","description":"","filename":"image18.png","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/589687d98f72d6cf73f1ee63.png"},{"id":92483868,"identity":"f84c9c76-c772-4bf7-a09e-62acab5dedcd","added_by":"auto","created_at":"2025-09-30 08:14:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3009054,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7730087/v1/c27d5bb1-d10a-4c51-9361-b8f9bae87df2.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAgricultural Land Management practices and their influence on microbial community composition and biological activity in soil\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eLand use and management practices are one of the most crucial factors influencing the physical, chemical, and biological properties of soil (Christel et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Meena \u0026amp; Rao, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Maharjan et al., \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Haghighi et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). It encompasses a range of human activity that directly affect soil health and are important driver of the changes in soil properties as well as microbial community. In addition to factors such as the parent material of the soil and environmental conditions, plant type, soil type, and, crucially, root exudates (Walker et al., \u003cspan citationid=\"CR140\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), these anthropogenic practices shape the functioning of soil mechanisms (Ramesh et al., \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Weil \u0026amp; Brady, 2017; Drenovsky et al., 2009). Essentially, soil physical, chemical and biological properties are interrelated and together linked to the changes in management practices (Chami et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lee et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe agricultural land system differs from a natural ecosystem in multiple aspects. Here, the influence is elevated since it is highly subjected to disturbance. Unlike natural ecosystems, soil properties in agricultural setting are subject to changes based on cultivation practices (Reilly et al., \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Particularly, among these, biological properties offer valuable insights to understand evolving state of soil processes, due to their responsive nature to changes in management and environmental conditions (Jat et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These biological parameters precede observable physiochemical changes in soil, thus serving as a reliable indicator of soil quality (Bhaduri et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kennedy \u0026amp; Stubbs, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The sensitive response helps monitor the shift in soil property and evaluate the impact of land management strategies and agricultural practices early.\u003c/p\u003e\u003cp\u003eLand management practices bring about changes in the microenvironment that regulate both, structure and activity of the soil microbial community (Lupwayi et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It includes changes in tillage practices, cropping patterns, fertilizer application, cover cropping, soil protection approaches, cropping systems, diversification etc. (Desta et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Grieve, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Specifically, studies conducted to understand the impact of agricultural land use show that interaction through changes in mulching (Djigal et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), no-tillage (Kabiri et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), conventional tillage (Balota et al., 2003), residue incorporation and decomposition (Bending et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), and fertilization (Hamel et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) play influential role on soil biology and soil microbial diversity (Zong et al., \u003cspan citationid=\"CR155\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Unlike forest or other undisturbed vegetation, under cultivation, the return of the plant litter and residues is less observed, hence reduced carbon and nutrient source changes the dynamics with regards to microbial functioning. The shift in microbial community structure and its role in the distribution of r-strategist, k-strategists, or pathogenic groups needs to be studied to understand the effect of the management strategies.\u003c/p\u003e\u003cp\u003eSoil microbial communities are the fundamental driver of soil ecological processes and biogeochemical cycles and are, therefore, essential to overall soil functioning. The microbial community plays an active role in nutrient cycling, organic matter decomposition, biotic and abiotic stress amelioration, respiration, biogeochemical cycle, crop production and other soil functions, which are substantially elevated in the rhizosphere (Griffiths \u0026amp; Philippot, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Mendes et al., \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Bissett et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Soil microbial populations adopt different life strategies that impact the microbial community structure under varying conditions leading to the dominance of copiotrophic or oligotrophic organisms (Chen et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) which is reflected in other soil processes. Microbial communities, made up of a vast range of preferential microbes, are sensitive to land use and management practices apart from vegetation, aboveground biomass, diversity, soil properties, and environmental changes (Christel et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bissett et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Bengtsson et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePlant species, above-ground biomass and cropping systems significantly influence soil biology and relative abundance of microbial phyla (Liu et al., 2019; Zhou et al., \u003cspan citationid=\"CR152\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The association between plants and microbes range from symbiotic and mycorrhizal associations to other detrimental associations (Dolatabadian, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Hence, the community structure and its activity are influenced mainly by the rooting structure, quality of plant residue, and release of carbon exudates from the above-ground vegetation. However, the scenario is still unclear in essential oil crops like Lavender. Moreover, comparing the microbial community structure in the same soil and region, under essential oil continuous cropping (Lavender), cereal crop rotation (wheat-maize) and uncultivated areas, can help in the assessment of soil properties, specifically biological properties under these systems.\u003c/p\u003e\u003cp\u003eFertilization affects microbial growth through the availability of nutrients in readily available forms helping microbial proliferation and heightened enzymatic activity (Hardy et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Chu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The association of long-term mineral fertilization, and organic amendments changes the composition of fungal and bacterial groups because of how different groups process the nutrients in the soil (Beauregard et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and changes the enzymatic activity in soil (Maschner et al., 2003). Under fertilized conditions, major nutrients increase, which positively affects the soil organic carbon, microbial proliferation and plant exudation (Guan et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Previous studies have documented a decline in organic matter under intensive agricultural cultivation and undermining of microbial diversity (Zhang et al., \u003cspan citationid=\"CR151\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and since SOC is directly linked to microbial activity, it is pertinent to understand these dynamics as well. On the other hand, inorganic fertilization may help increase the abundance but not the diversity. Under excessive N fertilizer use, bacterial diversity and carbon and nitrogen content are reduced in the soil (Verzeaux et al., \u003cspan citationid=\"CR137\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In agricultural soils, land management practices elevate loss of soil organic carbon through practices of residue removal and tillage but could stabilize SOC through practices such as cover cropping, zero tillage etc. (Sul et al., \u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Continuous cultivation demands higher nutrients to sustain plant production, which often leads to nutrient depletion, subsequently reducing soil microbial population and its activity.\u003c/p\u003e\u003cp\u003eCrop-related factors such as cropping pattern, cropping biomass, crop type, crop rotation (Guo et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), intercropping, and cropping system (Massaccesi et al., \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) shape microbial community due to plant behaviour and litter availability. Cropping diversification has indicated better result in improving soil aggregation, organic carbon, Nitrogen and microbial diversity (Tiemann et al., \u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The biomass changes rhizodeposition and increases exudates rich in low molecular weight carbon-rich compounds, sugars, amino acids, vitamins, etc., that activate microbial enzyme release enhancing soil enzymatic activities (Ma et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). For instance, specific microbial taxa, including Trichoderma and Rhizopus, have been identified as potential bioindicators of these changes (Silvestro et al., \u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In long-term wheat cultivation systems, reductions in nitrogen and phosphorus availability can lead to shifts, favouring groups that adopt slower growth strategies. This restructuring is linked to increased nutrient use efficiency and a decline in microbial biomass carbon (MBC) (Cruz et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). With regards to crop rotation, the key rhizosphere taxa is better at suppressing pathogens compared to a mono-cropping system, which has less diverse microbial abundance possibly due to association with the production of root exudates and compounds (Zhou et al., \u003cspan citationid=\"CR153\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn Bare soil, the lack of organic input aggravates the situation and has lower soil organic carbon, nutrient availability and low microbial abundance. In case of reduced and lack of Nitrogen fertilization, K strategists might dominate the microbial community (Cruz et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The strategies are also linked to soil carbon content and the C: N ratio, influencing carbon cycling (Osburn et al., \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Piton et al., \u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The metabolism of aboveground biomass (C3 or C4), also influences the accumulation of SOC where C4 metabolism may not accumulate high SOC due to quicker decomposition and turnover rate at higher temperatures. (Singh et al., \u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wand et al., \u003cspan citationid=\"CR141\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). pH could regulate soil microbial composition and enzymatic activities in soil (Zhong et al., 2024), which is again influenced by agricultural practices and quality of organic matter, and breakdown byproducts releasing organic acid, H\u0026thinsp;+\u0026thinsp;ions, and HCO3- ions (Guo et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Xiao et al., \u003cspan citationid=\"CR146\" class=\"CitationRef\"\u003e2022\u003c/span\u003e ; Jones et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Due to the dynamics between land management, cropping system, and soil biology, the nature of the response of the microbial community necessitates site-specific studies of management practices on soil microbial structure and soil health.\u003c/p\u003e\u003cp\u003eThe strategies adopted by the microbes present in soil are through multiple pathways of compound production, competition, modification of cellular membrane, metabolites, enzymatic production, or chemical signalling metabolisms etc. (Wang et al., \u003cspan citationid=\"CR142\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Higher release of simple organic carbon rich compounds from exudates and residue with low C: N ratio might lead to the dominance of microbial groups such as Pseudomonas, β- and the γ- sub-groups of proteobacteria that are copiotrophic in nature and efficiently utilize the compounds. This proliferation thereon can result in organic matter mineralization. On the contrary, microbes such as Ascomycota, Actinobacteria, Deltaproteobacteria, Basidiomycota, and myxobacteria etc., may increase in abundance under nutrient-scarce conditions and degradation of recalcitrant organic matter (Chen et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Bastian et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Bernard et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Practices of no-tillage and retention of residues in the field have been reported to increase organic Carbon and nitrogen levels and soil microbial activity, but the authors also found an increased incidence of pathogenic microbes (Pankhurst et al., \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Beneficial microbial groups, such as Bacillus, Trichoderma, Pseudomonas, etc., have been isolated and commercially applied to diversify the microbial community (Wang et al., \u003cspan citationid=\"CR142\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Tao et al., \u003cspan citationid=\"CR130\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSoil enzymes are sensitive to changes in land management practices, environment and soil properties like pH, organic matter, and nutrient availability (Neemisha \u0026amp; Sharma, 2022; Allison \u0026amp; Vitousek, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Dick \u0026amp; Tabatabai, 1993). Enzyme activities are an indication of the biochemical processes and have subsequent effects on the microbial community functioning (Moghimian et al., \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Both intracellular and extracellular enzymes in the soil, either, after synthesis/secretion by microbes, cell lysis, or stabilized in the soil matrixes, facilitate the chemical catalysis and biochemical breakdown of organic and inorganic compounds in soil matrixes (Nannipieri et al., \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Hence, although it may provide an indication of the soil's biological activity, we cannot equate it with microbial activity. Therefore, other forms of biological assessment may help in better assessment. For instance, when complex compounds are adequate and simple nutrients are scarce, enzyme production is expected to increase as microbial degradation occurs to access resources. However, enzyme activity may remain low under resource-limited conditions (Allison \u0026amp; Vitousek, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Localized studies can investigate the effect of specific management practices and allow for any modifications. Although the application of inorganic fertilizer is associated with an increase in the abundance of the microbial population, it may not have same impact on microbial diversity and richness (Dincă et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Hence, a combination of assessing biological studies, including enzyme activity and amplicon sequencing, can provide contextual insight into biological health for informed decision-making on long-term management strategies in agricultural soil.\u003c/p\u003e\u003cp\u003eBulgaria's agricultural production is dominated by cereal cultivation, where wheat production is the highest (European Commission, 2023). Similarly, it is the largest producer of lavender worldwide (Stanev et al., \u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). European Green Deal aims to make significant changes in the agricultural practices and nutrient management strategies of EU countries (European Commission, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Bulgarian agricultural setting provides an opportunity, with limited research on the interaction and influence of soil management and cropping systems on soil biological health, particularly the microbial community. Our study was conducted to study how structural differences in soil microbial communities vary across different agricultural land management systems. It also aims to provide insight into understanding the soil biology in a cereal-based agricultural system (with relatively diversified cropping and fertilization regime), in essential oil crop systems (under monoculture and longer cultivation), and in unmanaged agricultural land use system.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy site\u003c/h2\u003e\u003cp\u003eThis study was conducted in a long term experimental site adjacent to each other in the Research Station of Agricultural University, Plovdiv from 15th of April, 2025 to May 2025 (42\u0026deg;07'45.8\"N 24\u0026deg;48'03.9\"E). The annual rainfall in Plovdiv is 551 mm with annual average temperature at around 11.4 degree Celsius. Three sites subjected to different agricultural land management practices were selected for studying the influence of agricultural system in the soil microbial community structure and properties.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSoil Collection and Soil Sampling\u003c/h3\u003e\n\u003cp\u003eRandomized soil sampling approach was used to collect soil samples from each land management system in April 2025. Composite soil samples were collected from the 0 to 20 cm from the soil surface from each site separately, homogenized and packed into sampling bags. Soil samples were collected so as to be representative of the whole field. Once in the laboratory, the sample was air dried, sieved (\u0026lt;\u0026thinsp;2mm) and stored for further analysis. The fresh soil samples were for stored in refrigerator (-4 \u0026deg; celsius) for biological analysis and amplicon sequencing.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExperimental and Management system with their background history\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgricultural system\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eManagement practices\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCropping History\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFertilization History\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLavender cultivation system\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganic farming, inter-row mowing, minimal tillage, weed control\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePerennial \u003cem\u003eLavandula angustifolia\u003c/em\u003e (5\u0026thinsp;+\u0026thinsp;years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo synthetic fertilizers; compost or manure applied occasionally\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWheat based agricultural rotation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConventional tillage, crop rotation, herbicide and pesticide use\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWheat\u0026ndash;maize\u0026ndash;sunflower rotation over the past 6 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRegular application of NPK fertilizers and urea\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnmanaged area with grasses\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo tillage, no inputs, natural vegetation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDominated by perennial grasses and spontaneous herbs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo fertilization\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eSoil pH and Electrical Conductivity\u003c/h3\u003e\n\u003cp\u003e5 gram of air dried soil sample after sieving was taken and mixed with 25 ml of distilled water into 1:5 ratio. The mixture was shaken for 30 minutes and left to settle for 30 minutes. After sedimentation, the sample, was filtered and pH and EC measurements were taken using pH meter and EC meter (Rhoades, \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Thomas, \u003cspan citationid=\"CR132\" class=\"CitationRef\"\u003e1996\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eGrowth of Colony forming Units\u003c/h3\u003e\n\u003cp\u003ePreliminary probe study was conducted in December 2024 during the winter season to assess the microbial community present in the three sites. Various specialized nutrient media (Table\u0026nbsp;2) were prepared that catered the growth of differing microbial groups. 1 gram of fresh soil sample was weighted and 99 ml of sterile distilled water was added in a test tube for serial dilution method to form 1:100 ratio. The solution was shaken to mix uniformly and left to settle. Then, 1 ml of the solution was taken in another test tube and mixed with 99 ml of sterile distilled water to prepare dilution of 10\u003csup\u003e3\u003c/sup\u003e, 10\u003csup\u003e4\u003c/sup\u003e, and 10\u003csup\u003e5\u003c/sup\u003e solution. Following this, the sterile media after autoclaving at 121 \u0026deg; Celsius for 2 hours were plated and left to cool for a few hours. The diluted soil samples were plated in the solidified media under laminar air flow and incubated to observe colony growth.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSpecialized media and their composition\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedia\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecialized growth\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eComposition\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRose Bengal Agar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecialized fungal growth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePeptone, glucose, KH₂PO₄, MgSO₄, Rose Bengal dye, agar\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTryptic soy agar (TSA)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecialized bacterial growth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePancreatic digest of casein, enzymatic digest of soybean meal, NaCl, agar\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYeast extract agar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecialized Yeast Growth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYeast extract, peptone, glucose, agar\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAzotobacter Media\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN2 fixing\u0026nbsp; Bacteria Growth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGlucose, KH₂PO₄, MgSO₄, NaCl, CaCO₃, FeSO₄, agar\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePKV media\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhosphate solubilizing bacteria Growth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGlucose, tricalcium phosphate (Ca₃(PO₄)₂), (NH₄)₂SO₄, NaCl, MgSO₄, agar\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eActinomycetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecialized Actinomycetes growth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCasein, KNO₃, NaCl, MgSO₄, K₂HPO₄, agar\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSabouraud dextrose agar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecialized for Fungal and yeast growth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePeptone, dextrose (glucose), agar; acidic pH (~\u0026thinsp;5.6) to inhibit bacterial growth\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eDehydrogenase Activity\u003c/h3\u003e\n\u003cp\u003eThe dehydrogenase activity was estimated following Thalmann (1968) modified by Alef (1995). This estimation of Dehydrogenase activity is based on the reduction of Triphenyl Tetrazolium Chloride (TTC) to Triphenyl formazon (TPF) that is driven by microbes present in the soil sample. 1 grams of fresh soil was taken and placed in a test tube. To this 5 ml of 2,3,5- Triphenyl Tetrazolium Chloride (TTC) solution was added. Blank control was placed which included only 5 ml Tris buffer and no TTC solution. All treatments were replicated 3 times. These test tubes were incubated for 24 hours at 30 \u0026deg; Celsius. After incubation, 40 ml of acetone was added to each replicates and shaken to mix thoroughly after which the mixture was left at room temperature in the dark for 2 hours. The solution was then filtered and absorbance of the reduced TPF in filtrate was measured using spectrophotometer at wavelength of 546 nm. Special care was taken to conduct procedures under diffused light due to the sensitivity of TTC and TPF. Tris Buffer was prepared by adding 12.114 grams of TRIS and 648 ml of 0.1 M HCl which was made up to 1000 ml using distilled water.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eβ-Glucosidase Activity\u003c/h2\u003e\u003cp\u003eBeta Glucosidase activity was estimated according to Tatabatai (1982) modified by Alef and Nannipieri (1995). The estimation was based on the degradation of p-nitrophenyl-β-D-glucoside (PNG) to p- nitriphenol through microbe present in the soil. 1 gram of fresh soil was placed in volumetric flask. Then 0.25 ml of toluene was added to the sample following which 4 ml of buffer solution was added. Buffer solution was prepared by mixing from 21.1 g Tris, 11.6 g maleic acid, 14 g citric acid, 6.3 g boric acid, 500 ml of 1 M NaOH, and 1-liter distilled water. To the mixture 1 ml of p-nitrophenyl-β-D-glucoside (PNG) was added. The samples were mixed and then incubated for 1 hour at 37 degree Celsius. Following this, in the incubated soil, 1 ml calcium chloride (CaCl\u003csub\u003e2\u003c/sub\u003e) and 4 ml of Tris buffer (pH 12) was added and shaken to mix and filtered. The absorbance of the filtrate was then measured with spectrophotometer at 400 nm wavelength.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eBasal Soil Respiration Rate\u003c/h3\u003e\n\u003cp\u003eThe basal soil respiration was measured according to Alef (1995). 50 grams of fresh soil after removing organic residues was placed in a Jar. 20 ml of NaOH was measured in a beaker and placed inside the jar carefully without any contact and the lids were sealed. This was replicated 3 times. Similarly, for blank, only NaOH but no soil sample was used and replicated 3 times. The jars were placed in an incubator for 2 hour at 26 degree Celsius. After the exposure time, 1 ml Barium Chloride (BaCl\u003csub\u003e2\u003c/sub\u003e) was mixed with NaOH that leads to precipitation of carbonates forming Barium Carbonate. A few drops of 0.1% phenolphthalein was added to the mixture and the solution was titrated against 0.05M HCL until the colour changed from violet to colourless.\u003c/p\u003e\u003cp\u003eNaOH\u0026thinsp;+\u0026thinsp;CO2\u0026thinsp;=\u0026thinsp;Na2CO3\u0026thinsp;+\u0026thinsp;H2O\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:CO₂\\left(mg\\right)SW⁻\u0026sup1;t⁻\u0026sup1;=\\frac{\\left(Vo-V\\right)\\times\\:0.05\\times\\:22}{dw\\:\\times\\:t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhere, V\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;amount of HCL required for Blank,\u003c/p\u003e\u003cp\u003eV\u0026thinsp;=\u0026thinsp;amount of HCL required in soil, t\u0026thinsp;=\u0026thinsp;Incubation time (in hours), dwt\u0026thinsp;=\u0026thinsp;dry weight of 1g moist soil, 22\u0026thinsp;=\u0026thinsp;Equivalent weight of Carbon Dioxide (CO\u003csub\u003e2\u003c/sub\u003e). SW\u0026thinsp;=\u0026thinsp;Dry weight of soil in grams.\u003c/p\u003e\n\u003ch3\u003eGenomic Analysis\u003c/h3\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eDNA Extraction\u003c/h2\u003e\u003cp\u003eGenomic DNA was extracted from fresh soil samples using the DNeasy PowerSoil Pro Kit (Qiagen, Germany), following the manufacturer protocol. Approximately 0.25 g of homogenized soil was used for each extraction. To ensure consistency and avoid DNA degradation, all extractions were performed under sterile conditions and stored at \u0026minus;\u0026thinsp;20\u0026deg;C until downstream processing. The quality and quantity of the extracted DNA were assessed using a NanoDrop\u0026trade; 2000 spectrophotometer (Thermo Fisher Scientific, USA) and verified by agarose gel electrophoresis. DNA samples with A260/280 ratios between 1.8 and 2.0 and no visible degradation were selected for sequencing.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eAmplicon Sequencing\u003c/h2\u003e\u003cp\u003eThe V3\u0026ndash;V4 hypervariable regions of the 16S rRNA gene were amplified using universal primers 341F (5\u0026prime;-CCTACGGGNGGCWGCAG-3\u0026prime;) and 806R (5\u0026prime;-GACTACHVGGGTATCTAATCC-3\u0026prime;) for bacterial community analysis. PCR reactions were performed for each sample using high-fidelity polymerase (Phusion High-Fidelity DNA Polymerase, New England Biolabs) to minimize amplification errors. The amplicons were purified using AMPure XP beads (Beckman Coulter), and library preparation was performed using the Illumina Nextera XT DNA Library Preparation Kit. Paired-end sequencing (2 \u0026times; 300 bp) was carried out on the Illumina MiSeq platform at [Novogene, UK], generating high-throughput sequence data for microbial community profiling.\u003c/p\u003e\u003cp\u003eRaw sequence reads were demultiplexed, quality-filtered, and processed using the QIIME2 (Quantitative Insights Into Microbial Ecology, version 2024.2) pipeline. Chimeric sequences were removed using DADA2, and the remaining high-quality sequences were clustered into amplicon sequence variants (ASVs). Taxonomic classification was assigned using the SILVA v138 database for bacterial sequences and the UNITE database for fungal sequences.\u003c/p\u003e\u003cp\u003eAlpha and beta diversity indices (Shannon, Simpson, Bray-Curtis) were calculated, and community structure differences were visualized through principal coordinate analysis (PCoA) and non-metric multidimensional scaling (NMDS). Phylogenetic distances were assessed using UniFrac metrics to compare microbial community relatedness across different land use systems.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe raw sequence data generated from this study have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject PRJNA1292883. Metadata files and QIIME2 artifacts are available upon reasonable request to the corresponding author.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThe influence of land management on soil properties were assessed using one way ANOVA to check for significance. The data were checked for normality of distribution using Shapiro-wilk test and Levene\u0026rsquo;s test was used to check the normality/homogeniety of variance in observed data. Both of these tests were done using package car (Fox et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Then, in case the assumption of equal variance across group did not meet (i.e. levene test significant meaning the variance in a group is different), data were log transformed, and further analysis were conducted. Subsequently, the multiple comparison of mean between the treatments was further analysed with posthoc test using Tukey Honestly Significant Difference test using agricolae package (Mendiburu, \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The analysis was conducted at 5% significance level (p\u0026thinsp;\u0026le;\u0026thinsp;0.05). All analytical tests were conducted in R Studio version 2024.04.1. The sequencing data were analysed using QIIME2 following standard DADA2 downstream analysis. The plots were prepared using ggplot2 package.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eSoil pH and EC under three land management system\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe agricultural management system had significant effect on soil pH. Lavender cultivation system exhibited the highest soil pH (7.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0173), followed closely by the wheat-based rotation (7.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0208), with no significant difference between them. The unmanaged area with wild growth showed a significantly lower pH (7.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0656) compared to both managed systems. This suggests that agricultural management, particularly perennial systems like lavender cultivation, may help maintain slightly more alkaline soil conditions, possibly due to organic amendments or reduced nutrient depletion.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eLikewise, we observed that land management practices had significant impact on the Soil Electrical Conductivity (EC) of the soil. EC was significantly higher in the lavender system (0.178\u0026thinsp;\u0026plusmn;\u0026thinsp;0.013 mmho/cm). On the other hand, unmanaged grassland (0.142\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0055 mmho/cm) and wheat-based rotation system (127\u0026thinsp;\u0026plusmn;\u0026thinsp;0.006 mmho/cm) had similar and significantly lower EC values.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eEnzyme activities under differing Agricultural Land use Management\u003c/h2\u003e\u003cp\u003eThe influence of land management practices on both Dehydrogenase activity and β-Glucosidase Activity across the sampled sites were significant (p\u0026thinsp;\u0026le;\u0026thinsp;0.05). The wheat based rotation exhibited highest dehydrogenase activity (0.489\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0162) followed by significantly lower Lavender cultivation (0.380\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0172) and unmanaged land (0.357\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00885).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDehydrogenase and Beta-Glucosidase activity under different Agricultural system\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgricultural Land Use system\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDehydrogenase Activity (\u0026micro;g TPF/g Soil)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eβ-Glucosidase Activity (\u0026micro;g pNP/g soil)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLavender cultivation system\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.380\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0172\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.97\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWheat based Rotation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.489\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0162\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.665\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnmanaged area\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.357\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00885\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe values reported are Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE and are significant at p\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWith regards to β-Glucosidase Activity, Lavender Cultivation system exhibited high enzymatic activity (29.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.97) followed closely by Wheat based rotation (25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.665). The lowest enzymatic activity was observed in unmanaged land (14.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eBasal Soil Respiration under three Agricultural system\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBasal Soil Respiration and Soil Moisture under different Agricultural system\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgricultural Land Use system\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBasal Soil Respiration rate (mgCO2/gm/hr)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLavender cultivation system\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0942\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWheat based Rotation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0976\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnmanaged area with wild grass\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.299\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe values reported are Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and are significant at p\u0026thinsp;\u0026le;\u0026thinsp;0.05. Different letters indicate significant difference between the means.\u003c/p\u003e\u003cp\u003eSimilarly, the effect of agricultural system was exhibited in the basal soil respiration with highest CO2 production in unmanaged area with presence of wild grasses (5.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.299\u003csup\u003ea\u003c/sup\u003e). The effect of land management on basal soil respiration was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Soil respiration under Lavender monoculture (4.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0942\u003csup\u003eb\u003c/sup\u003e) and wheat based rotation (4.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.0976\u003csup\u003eb\u003c/sup\u003e) were significantly lower in comparison to unmanaged area. However, soil respiration under these two system were statistically similar to each other.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eMicroorganisms and Colony Forming Units different Agricultural Land use Management\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe found significant effect of land management on the growth of soil microbe in artificial media. Among specialized media, phosphate solubilizing bacteria (Pikovskaya\u0026rsquo;s media) and Nitrogen solubilizing bacteria (Azotobacter media), both exhibited significant impact of land management on their growth habit (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For instance, higher number of microbial growth in Azotobacter media was observed in Wheat based rotation, followed by statistically similar unmanaged area. The lowest colony count was observed in lavender cultivation. Likewise, highest colony growth of phosphate solubilizing bacteria was on Lavender cultivation and Wheat based rotation with lowest record in unmanaged area. Actinomycetes colonies were higher in Wheat based rotation and Lavender cultivation which was statistically higher than unmanaged area.\u003c/p\u003e\u003cp\u003eWe did not find significant impact of land management in the colony growth on tryptic soy agar (for general bacterial growth) and Sabouraud dextrose agar (fungal growth). Still, with TSA we found higher colonies in Wheat based rotation, and lavender cultivation relatively. In case of Sabouraud, growth was only observed in wheat based rotation, and no growth on other land management. The growth observed in Rose Bengal agar was significantly higher than both wheat based rotation and unmanaged area.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eColony forming units (CFU) growth under specialized media\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eColony Forming Units\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eLand Management System\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLavender cultivation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWheat based rotation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnmanaged area\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN2 fixing bacterial media (Azotobacter)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.74\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.39\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05, *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eActinomycetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.113\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.13\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.74\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05, *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRose Bengal Agar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.47\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.55\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.39\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05, *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTryptic Soy Agar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.46\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.53\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.33\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05, ns\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhosphate solubilizing Bacteria Media\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.74\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSabouraud\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.82\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;0.05, ns\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e* indicates significant effect of land management system at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. ns\u0026thinsp;=\u0026thinsp;nonsignificant, Differing letter indicates statistically different mean values of measured properties.\u003c/p\u003e\u003cp\u003eThe culturing of soil microorganisms on specialized media exhibited differing result that indicated the significant influence of land management on colony forming units of soil microbes in artificial media. The N2 fixing bacterial growth media exhibited significantly higher CFUs in Wheat based rotation followed by Unmanaged area (statistically similar but lower) with low colony growth in Lavender (significantly lower). Actinomycetes colony growth was higher and statistically similar in wheat based rotation and lavender cultivated soil whereas it was significantly lower in unmanaged area. Likewise, microbial growth in Rose Bengal agar was also significantly different among the management practices. It was significantly higher in wheat rotation, meanwhile the other two has similar but statistically lower colonies growth. The colony growth of microbes in pikovskaya\u0026rsquo;s media was higher significantly, significantly high colonies were observed in lavender cultivation. This was followed by statistically similar but lower CFU in wheat based rotation. The lowest colonies of p solubilizing bacteria were present in unmanaged soil. In case of growth in tryptic soy agar, and sabouraud dextrose agar, colony growth were not significantly different among the different land management system.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eGravimetric water Content under different land management\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSoil Moisture content of Fresh Soil Under different agricultural system\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgricultural Land Use system\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSoil Moisture Content (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLavender cultivation system\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.208\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWheat based Rotation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.111\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnmanaged area with wild grass\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.0 \u0026plusmn; 0.347\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe values reported are Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and are significant at p\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003eMeanwhile, Gravimetric Water Content (GWC) of the field soil under differing land management system varied between the soil subjected to these practices significantly (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005). Highest gravimetric content was observed under unmanaged area with wild grasses (28.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.347\u003csup\u003ea\u003c/sup\u003e). This was followed by Wheat based rotation system (25.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.111\u003csup\u003eb\u003c/sup\u003e) and Lavender Cultivation system (21.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.208\u003csup\u003ec\u003c/sup\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe values reported are Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD and are significant at p\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eSoil Moisture and its relationship with Basal Soil Respiration\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe linear regression analysis showcased nonsignificant but positive relationship (R2\u0026thinsp;=\u0026thinsp;0.45, p\u0026thinsp;\u0026gt;\u0026thinsp;0 .05) between the soil moisture content and basal soil respiration. This also showcased distinct differentiation of land use and its moisture content in the soil (Fig.\u0026nbsp;6).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eMetagenomic Characterization of Soil Bacterial Community\u003c/h2\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eMetagenomic Sequencing and Quality Assessment of the Soil samples\u003c/h2\u003e\u003cp\u003eAll of our soil samples showcased high sequence quality, with over 95% score of Q30. High number or base quality is an indication of reliable base calls (Ewing and Green, 1998). After quality filtering a total of 192381 paired-end reads were clustered into OTUs. The lower number of chimeric reads, and higher number of qualified reads was suitable for metagenomics profiling through downstream analysis. The GC content varied across the samples. It was higher in Lavender Cultivation (57.73%) in comparison to Wheat based rotation (56.13%), with lowest in unmanaged area (53.91%).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eRelative Abundance of microbial groups under three land management\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe taxonomic classification was conducted and ten most abundant phyla in each land management were identified and then used to construct a histogram to present their relative abundance in the sample. The representation allows a comparative analysis of the dominant bacterial phyla between these land management systems. We found that the relative abundance varied across the samples (Fig.\u0026nbsp;10). Proteobacteria (54.75%) was the dominant phyla observed in unmanaged land followed by Acidobacteriota. Incase of Lavender cultivation, Actinobacteriota (34.20%), Proteobacteria (20.56%), and Acidobacteriota (20.11%) were the most abundant phyla with high proportional distribution. This was also similar in Wheat based rotation, where Acidobacteriota (28.73%), Actinobacteriota (19.97%) and Proteobacteria (17.5%) showed a higher proportion but contributed lower to the total relative dominance. This visualization provides and understanding into the distribution and abundance of major bacterial phyla in soils subjected to differing land management practices.\u003c/p\u003e\u003cp\u003eAt Genus level, among the top 10 abundant genus, Masilia (12.28%), Sphingomonas (7.37%), Pedobacter (5.50%), Pseudomonas (4.45%), Lysobacter (3.10%) were abundant in unmanaged area. However, this distribution in managed area was at a relatively lower percentage in Lavender cultivation and Wheat based rotation. For instance, Gaiella (5.42%), and Sphingomonas (5.19%) were abundant in Lavender based cultivation whereas, this was much lower in wheat based rotation Gaiella (2.07%), and Sphingomonas (2.80%). In wheat based distribution, we found well distributed microbial population while looking at highly abundant 10 genus, occupying over 1% abundance, except for 2 Genus (Fig.\u0026nbsp;10).\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eMicrobial Community Composition across different Land management\u003c/h2\u003e\u003cp\u003eSimilarly, the Venn diagram was created to observe the distribution of shared and unique feature sequences i.e. operational taxonomic units (OTUs) or amplicon sequence variants (ASVs) across different land management practices. The highest feature sequences were observed in Lavender cultivation with 1245 unique feature sequences followed by 1140 unique feature sequences indicating distinct a microbial community presence. The lowest unique feature sequence (871) were present in unmanaged areas. Over all, a total of 4117 OTUs were observed across the three land management systems. A total of 271 feature sequences were shared among the three management system indicating the core microbiome apart from the unique feature sequences. A higher share between wheat based rotation and lavender cultivation was observed with 305 shared features followed by wheat based rotation and unmanaged area (199). Low (86) feature sequences were shared between unmanaged area and lavender cultivation which indicated the distinct differences in microbial community structure between these land management practices.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003eTernary Plot Analysis of Dominant Bacterial Orders\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe ternary plot of the dominant orders of microbial organisms also demonstrated a distinct distribution pattern of bacterial orders across the land management systems. Here, we found a strong association of Burkholderiales with unmanaged areas. It was the most dominant order in unmanaged soil. Other abundant orders were Sphingomonadales and Sphingobacteriales. Meanwhile, association of Vicinamibacterales was higher with both lavender cultivation system and Wheat based rotation. On the other hand, with wheat based rotation we found relatively higher abundance of Vicinamibacterales, Burkholderiales and Chitinophagales. The distribution of some orders around the centroid also indicates balanced distribution of some microbes across all the land management systems.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003eBacterial Community Diversity Indices across land management\u003c/h2\u003e\u003cdiv id=\"Sec28\" class=\"Section4\"\u003e\u003ch2\u003eAlpha Diversity Indices\u003c/h2\u003e\u003cp\u003eThe Alpha diversity analysis was conducted to study the microbial community structure through the richness and the evenness of bacterial communities under soil subjected to differing land management system.\u003c/p\u003e\u003cp\u003eMicrobial community richness was estimated using Chao1 index. Here, the higher index indicated higher microbial richness and abundancy of species. The highest chao1 index was in Wheat based rotation (1928.703) followed by lavender cultivation (1917.316). The lowest chao1 index was observed in unmanaged area (1427). In line with this we also found higher observed features in Wheat based rotation and Lavender cultivation (1915 and 1907 respectively).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAmong diversity indices, Shannon index that accounts for richness and evenness of the microbial organisms, exhibited higher values for Lavender Cultivation (9.806) and Wheat based rotation (9.676) with relatively lower index in unmanaged soil at 8.675. Hence higher diversity was observed in Lavender and wheat based rotation. On the other hand, low dominance in both lavender cultivation (0.002) and wheat base rotation (0.003) indicates there was very low dominance of any single taxon in these soils, which was in contrast to the dominance value of 0.008 in unmanaged soil. Meanwhile, Simpson index indicated a higher diversity across all land management with 0.998 in Lavender, 0.997 in wheat based rotation and 0.992 in unmanaged soil with relatively higher diversity in managed soils. Pielou\u0026rsquo;s Evenness also reflected the evenness of species abundance in Lavender cultivation and Wheat based rotation with relatively lower Pielou\u0026rsquo;s evenness. This leads to an understanding of how management and fertilization regime helps increase the microbial richness in soil. Whereas, the higher dominance and low Simpson values are an indication of microbial community dominated by fewer taxa in unmanaged soil.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003eBeta Diversity Indices\u003c/h2\u003e\u003cp\u003eThe Beta Diversity indices were calculated with both weighted UniFrac and Unweighted UniFrac distance metrics that analysed the dissimilarities between different land management systems. Weighted UniFrac is based on the phylogeny and abundance based method whereas Unweighted UniFrac is based on the presence and absence based method.\u003c/p\u003e\u003cp\u003eWe found higher dissimilarity observation with unweighted UniFrac distance matrix compared to Weighted UniFrac distance matrix. For instance, we found highest dissimilarity between the unmanaged soil and Lavender cultivation with Weighted UniFrac distance of 0.427 and Unweighted UniFrac of 0.580, indicating substantial differences in both community composition and abundance structure. We also found higher dissimilarity between unmanaged soil and wheat based rotation with UniFrac distance of 0.362 (weighted) and 0.520 (unweighted). However in case of Lavender cultivation and Wheat based rotation, we found relatively lower degree of dissimilarity with 0.267 (Weighted) and 0.536 (Unweighted). This may suggest a partial overlap or similarity in community structure between managed soil with nutrient availability, tillage, plantation and enriched taxa with plant root influence.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePrincipal Coordinates Analysis (PCoA)\u003c/h3\u003e\n\u003cp\u003e\u003c/p\u003e\u003cp\u003ePrincipal Coordinates Analysis (PCoA) helps in understanding the differences in microbial community composition with both Weighted and Unwieghted UniFrac distances. In Weighted UniFrac distance, the first principal coordinate (PC1) explained 75.09% of the total variance and PC2 explained 24.91% of the variance. This is crucial because there is a distinct separation of the effect of land management on the microbial communities. The Weighted UniFrac plot that also accounts for relative abundance, showed clear distinction between the land management systems with distinct microbial communities. PC1 (56.65%) and PC2 (43.35%) together explained the entire variation, suggesting strong influence of both species composition and abundance on microbial community structure.\u003c/p\u003e\u003cdiv id=\"Sec31\" class=\"Section2\"\u003e\u003ch2\u003eSoil Microbial Function Prediction of Soil Bacterial Communities\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFAPROTAX-based functional profiling are significant in analysing and predicting the differences in microbial function of the microbial taxa in a community. We found that in unmanaged area, functions associated with aromatic compound degradation, such as chitinolysis, ureolysis, cellulolysis etc. were enriched. This was relatively less in Lavender and markedly reduced in wheat based rotation. This also indicates that the soil under unmanaged area with native taxa may dominate and have biodegradative potential. On the other hand, in cultivated areas, functions associated with photosynthesis such that of photoautotrophy, oxygenic phototautotrophy which may be linked with root associated energy metabolism. In wheat based rotation we found that the functions associated with Nitrogen cycling such as nitrogen reduction, nitrification, nitrogen and nitrate respiration were present. This in an indication of the nitrogen transformation process with roles of microbes in Nitrogen cycling. Furthermore, functions associated with pathogen and symbionts were higher in unmanaged area indicating the suppression or absence of those microbial taxa in managed areas.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec32\" class=\"Section2\"\u003e\u003ch2\u003eTaxonomic Abundance Cluster heat Map of soil Bacterial Community\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe heat map of most abundant 35 phyla showed significant changes in microbial community due to the influence of land management system. In unmanaged area, we found that Proteobacteria (54.75%) dominated the microbial community that was followed by Bacteroidata and Acidobacteria. However, in lavender cultivation we found Actinobacteriota as the dominant class with 34.20% abundance, which was followed by lower (20.56%) Proteobacteria and Acidobacteriota (20.11%). The highest proportion of Chloroflexi (11.61%) and Gemmatimonadota (5.21%) was also observed in Lavender cultivated soil as well.\u003c/p\u003e\u003cp\u003eOn the other hand, with wheat based observation, Acidobacteriota (28.73%), Actinobacteriota (19.97%) and Proteobacteria (17.50%) made up sort of balanced distribution of microbial phyla due to its influence. We found that Wheat based rotation formed a distinct cluster, indicating a unique microbial community, enriched in phyla such as Abditibacteriota, Planctomycetota, Verrucomicrobiota, Acidobacteriota, and WS2. Lavender cultivation exhibited high abundance of Myxococcota, Thermoplasmatota, and Actinobacteriota, with lower levels of Proteobacteria and Bacteroidota compared to unmanaged soil. Unmanaged soil however showed strong representation of Proteobacteria, Bacteroidota, and Bdellovibrionota, while exhibiting reduced levels of Firmicutes and Myxococcota. Hierarchical clustering grouped Lavender cultivation system and unmanaged soil microbial community closer together, while wheat based rotation stood out as compositionally distinct. At species level, a general diversified pattern was observed with slightly higher diversity under Lavender cultivation. Since the relative abundance of the top 10 species comprised a low percentage, \u0026lsquo;others\u0026rsquo; occupied 98.18% in Lavender, followed by unmanaged land (96.53%) and wheat-based rotation (95.98%). For instance, \u003cem\u003eNitrospira japonica\u003c/em\u003e and Gemmatimonadetes bacterium showed an increase in relative abundance under Lavender. A higher percentage of \u003cem\u003eLysobacter sp.\u003c/em\u003e, \u003cem\u003eAdhaeribacter terrae\u003c/em\u003e, \u003cem\u003eCaenimonas sp\u003c/em\u003e. and \u003cem\u003eSolitalea koreensis\u003c/em\u003e in uncultivated areas was observed. \u003cem\u003eNitrospira japonica\u003c/em\u003e and \u003cem\u003eActinobacterium WWH12\u003c/em\u003e were higher in cultivated areas.\u003c/p\u003e\u003cdiv id=\"Sec33\" class=\"Section3\"\u003e\u003ch2\u003ePhylogenetic tree of Soil Bacterial Community\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA phylogenetic tree of 100 most abundant genera was constructed to exhibit the evolutionary relationship of the microbial taxa in a community and its link with the genus present in the soil. We found that majority of the microbes present belonged to Proteobacteria, and Bacteroidata phyla. For instance, genera such as Massilia, Methylotenera, Pseudomonas, Sphingomonas which originated from Proteobacteria phylum were dominant in Uncultivated and unmanaged area. Likewise, we also found genus like Gemmatimonas, Candidatus Nitrososphaera etc evolving without following the typical evolutionary tree.\u003c/p\u003e\u003cp\u003eMeanwhile, genera such as Rubrobacter (evolved from Phyla Actinobacteriota), Bacillus (evolved from Phyla Firmicutes), Nitrospira (evolved from Phyla Nitrospirota), Bryobacter (evolved from Acidobacteriota) were abundantly present in wheat based rotation. In case of Lavender cultivation we found that genera such as Gemmatimonas (Gemmatimonadota), MND1 and Sphingomonas (from Proteobacteria) were abundant. Along with that, here we observed a higher incidence of genus from phyla Actinobacteriota, as well as Proteobacteria with significant abundance of Gaiella, Agromyces, Mycobacterium, Streptomyces and Iamia.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec35\" class=\"Section2\"\u003e\u003ch2\u003eThe influence of soil management system on Soil Parameters\u003c/h2\u003e\u003cp\u003eAgricultural land management practices have a significant effect on the physicochemical and biological parameters of the soil. In our study, we found that Land management practices have a significant impact (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) on the pH and the EC of the soil (Table\u0026nbsp;3). The slightly lower pH observed under an unmanaged area with perennial wild grasses and tree cover can be attributed to the type of organic matter, its decomposition and the leaching of positive ions in the soil. For instance, the continuous input of organic litter over the years can release H\u0026thinsp;+\u0026thinsp;ions into the soil solution, which increases the soil acidity (Hong et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). And since the quality of biomass differs in its decomposition rate, it also affects the release of ions and weak acids and can shift the soil acidity. However, even though the difference in pH was significant in our study, pH across the sampling sites was neutral to alkaline.\u003c/p\u003e\u003cp\u003eSoil pH is affected by anthropogenic factors, environmental factors, and biomass type, which varies with slight changes in scenario (Hong et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Fabian et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Our finding of slightly lower pH in unmanaged areas with perennial cover is in line with Fabian et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), who reported that soil under perennial grass cover has lower pH than cultivated soil with regular tillage. The parent material and the soil type play a crucial role in the regulation of soil pH (Fabian et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Hence, multiple studies under different temperature and biomass variations would help assess the impact of these factors on physiochemical parameters.\u003c/p\u003e\u003cp\u003eBoth lavender cultivation and wheat-based systems maintained higher, more neutral-to-alkaline soil pH, likely due to management practices such as liming, fertilization, or organic matter addition. The uncultivated area tended to have lower pH, reflecting natural leaching, absence of amendments, and heterogeneity in vegetation and soil processes. This suggests that agricultural management stabilizes soil chemical properties, which can be beneficial for plant growth and microbial functioning. Our finding of higher pH aligns with the findings of Cai et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which indicated higher yield and increase in pH with manure application compared to fertilizer.\u003c/p\u003e\u003cp\u003eSoil pH can serve as an indicator of microbial regulation since its influence on soil microbial diversity has been reported extensively (Malik et al., \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Tripathi et al., \u003cspan citationid=\"CR134\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). It may result in stochastic clustering of bacterial communities or a much deterministic clustering based on the soil pH, although the actual mechanism is not clear (Tripathi et al., \u003cspan citationid=\"CR134\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Hence, regulation of soil pH or drastic shift to extreme pH, particularly due to anthropogenic activity, could provide insights into the practices and their role in microbial community functioning along with microbial characterization. The monitoring of long-term pH under unmanaged and managed land might study acidification and alkalinity.\u003c/p\u003e\u003cp\u003eLand use strongly influences soil salinity, as reflected by EC values (Table\u0026nbsp;3). EC is the measure of the concentration of ions in soil. Overall, our findings were that across all land management, the soil was non-saline (0\u0026thinsp;\u0026lt;\u0026thinsp;2 dS/m). However, the Lavender cultivation system showed significantly higher soil salinity compared to the other two land management, which might be due to its perennial nature, potential build-up of ions from reduced leaching, or specific soil amendments. The amendments of compost and manure addition provide a higher negatively charged surface for positive salt ions (Cooper et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Since lavender cultivation is associated with higher EC, monitoring for potential long-term salinity effects may be needed. Both the uncultivated grassland and wheat-based systems maintained lower EC levels, indicating minimal salinization risk under these land uses. The lower EC in wheat-based rotation, despite fertilization, might have resulted from greater nutrient removal through harvesting or seasonal leaching.\u003c/p\u003e\u003cp\u003eThe higher EC may be a result of the addition of organic manure and compost (in Lavender) and the presence of organic matter in unmanaged plots. The increased adsorption area of soil humus complexes increases the cation exchange capacity, which subsequently affects the EC (Husson et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Uncultivated and wheat-rotation systems support lower and more stable EC levels, contributing to more favourable conditions for soil microbial activity and plant growth.\u003c/p\u003e\u003cp\u003eMoreover, soil type characteristics such as soil type and structure also play a significant role in the moisture evaporation in soil (An et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Our study does not have the resources to discuss this aspect. However, this increase in evaporation is possible as there was no provision for mulching in Lavender. Along with this, the addition of manure and compost regularly increases the CEC of the soil, which in turn could increase the soil EC. This is reflected by comparatively lower moisture in Lavender cultivation, and we believe it could have played some role in relatively higher EC in the soil. On the other hand, although rich in organic matter, the accumulation of litter in unmanaged land also acted as an organic mulch, preventing moisture loss and could have regulated the EC more effectively. This could be the differentiator in the differences of EC between these two land management types. For instance, Husson et al. (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) also documented a positive relationship between EC and soil texture, organic matter and CEC of the soil. This is also similar to our findings of higher EC in lavender cultivation and unmanaged areas.\u003c/p\u003e\u003cp\u003eYear-round fertilization and removal of residue after every crop cycle have shown a significant impact on both the pH and EC of the soil. This is in comparison to unmanaged land with wild growth, where the litter enters the soil as a source of organic matter every year. Hence, in the case of Lavender residue, quality might have played a significant role in the soil. Wheat cultivation and unmanaged areas with grass support stable, low-salinity soils with slightly alkaline pH are beneficial for microbial and plant health. In contrast, the Lavender system, while still within neutral pH, shows signs of higher salinity, which may affect soil biological activity and long-term sustainability. These findings emphasize the positive impact of low-input and perennial systems on maintaining soil chemical balance.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSoil respiration and its relationship with moisture content across agricultural system\u003c/h3\u003e\n\u003cp\u003eOur study found that differing land management have significant influence on the soil respiration and the gravimetric water content. The higher moisture content in the unmanaged soil might be due to the accumulation of plant residue of the wild grasses and leaves that functioned as a mulch layer (\u003cb\u003eError! Reference source not found.\u003c/b\u003e). Soil respiration is a representative indicator of soil microbial activity and organic matter mineralization (Vanhala et al., \u003cspan citationid=\"CR135\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Previous studies have indicated that the water holding capacity of soil rich in organic matter increases in comparison to soil that lacks organic matter (Djigal et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Besides the organic layer, organic matter prevents the evapotranspiration loss of soil, increases moisture retention, reduces runoff, and influences the microbial functioning in soil (Fang et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Coppens et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Moreover, it is also likely that the soil was under no tillage regime that increased its moisture content. Tillage is linked with disruption of soil structure, exposure of soil micro and macro pores and loss of soil moisture with no protective organic mulch. However, the relationship of the tillage system and the porosity of soil is directed by the soil texture, and under no-tillage areas, the retention of soil moisture is higher (Feiziene et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe results on CO2 evolution due to management changes have not been uniform, with differing site-specific results (Feiziene et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Franzluebbers et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). In our case, however, we observed higher CO2 evolution with perennial grass cover and shrubs under unmanaged areas. The presence of high lignin organic residue has lower carbon use efficiency and may result in higher soil respiration (Almagro et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It is also possible that the root structure of wild grasses and shrubs below 2mm might have influenced CO2 production, which was different from the lower amount in other land management. The role of diversity in increasing soil respiration has also been documented (Madritch \u0026amp; Hunter, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eApart from this, the metabolic quotient (qCO2), the ratio of respiration to microbial biomass, might have shed some more light on understanding the greater energy use efficiency of the microbe or indicate the growth habit of the microbial community (Maeder et al., 2002). For instance, the presence of grasses and deciduous plants will result in a higher decomposition rate and less stabilization of recalcitrant organic matter, which increases CO2 production in soil (Howard \u0026amp; Howard, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Hence, the utilization of mature compost and manure applications, such as our lavender cultivation system, may be help moderate carbon stabilization while stimulating microbial growth in the soil. Besides, a record of decrease in soil respiration may happen in the case of compost-amended soils as time passes due to a decrease in SOC and labile carbon fraction (Kowaljow et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe relationship between soil respiration and gravimetric water content was high (R2\u0026thinsp;=\u0026thinsp;0.45, p\u0026thinsp;\u0026gt;\u0026thinsp;0.05); however, it was not statistically significant (Fig.\u0026nbsp;6). This indicates a positive relationship between soil respiration rate and soil moisture, with a positive influence of soil moisture on the soil respiration rate. Our results are similar to the findings by Howard and Howard (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) and Gerenyu et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), who reported that an increase in soil moisture up to an optimal point increases the CO2 evolution rate in a wide range of soils. However, soil respiration is largely influenced by soil temperature, and the organic matter of the soil and changes in this dynamic complex bring variation in the evolution rate (Ren et al., \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Franzluebbers et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). The presence of readily degradable and degradation-resistant compounds also impacts the soil microbial functioning. Hence, further studies on the components involved will provide a much clearer and more comprehensive understanding.\u003c/p\u003e\u003cp\u003eAlthough with an increase in CO2 in uncultivated areas, higher enzyme activity would be expected; however, balanced mineral fertilization with rotation (in wheat) and application of compost and manure (in Lavender) showcased higher enzymatic activity and carbon stabilization from an initial perspective. However, further studies are necessary to understand the long-term impact on soil biology.\u003c/p\u003e\u003cdiv id=\"Sec37\" class=\"Section2\"\u003e\u003ch2\u003eEnzymatic activities across different agricultural system\u003c/h2\u003e\u003cp\u003eSoil enzyme activities are a strong indicator of decomposition and microbial and soil biological health in that they reflect the biochemical reaction in the soil (Sinsabaugh et al., 2008). Our results indicate that land management significantly affects the enzymatic activity in the soil (Table\u0026nbsp;4). We found significantly higher Dehydrogenase and β-Glucosidase activity under Lavender cultivation with the application of mature manure and compost. Organic amendments with manure and compost often lead to positive effects on soil physical properties, nutrient availability and biology (Marschner et al., \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). These findings are similar to the findings of elevated enzymatic activity after the application of farm yard manure, organic amendments and balanced NPK application by Hu et al. (2014) and Marschner et al. (\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, the enzymatic activity is affected by the decomposition rate and the quality of aboveground and lower-ground biomass. The lower enzymatic activity observed in unmanaged areas with wild growth can be attributed to the heterogeneity of the litter present, which may have a slow decomposition rate, which is reflected in the enzymatic activity. For instance, C: N ratio of the residue influences the enzyme production and activity. The lower C: N ratio in agricultural soil may increase the enzymatic activity (Zhang et al., \u003cspan citationid=\"CR150\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBesides the influence of litter C: N ratio in enzymatic activity, the quality of organic matter and crop type also have the ability to shape the microbial community (Wagner et al., \u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Areas rich in initial fresh litter that are easily degradable may lead to higher enzymatic activity and assemblance of wider microbial groups, while areas rich in recalcitrant litter with wider C: N ratio can lead to assemblance of narrow microbial groups that can decompose and shape the microbial community (Bai et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Marschner et al., 2002). The assessment of Dehydrogenase and β-glucosidase is crucial in carbon cycling since this enzyme of two different classes are involved in the oxidative and hydrolytic breakdown of complex compounds.\u003c/p\u003e\u003cp\u003eFurthermore, the availability of nutrients and the easily degradable compounds in compost in the case of Lavender cultivation could have increased enzymatic production. The significantly high enzymatic activity in Wheat-based rotation might be due to the availability of easily available mineral nutrients to microbial communities. This leads to the easy proliferation of microbial populations, which is reflected in soil enzymatic activity. Likewise, the addition of residue and year-round application of compost and manure leads to elevated enzymatic activity. The Nitrogen availability is considered a driver of enzymatic activity, with an excess amount of Nitrogen available for plant and microbial growth (Curtright \u0026amp; Tiemann, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe enzymatic activity is also influenced by the C: N ratio of the residue in the soil. The rate of decomposition varies with the carbon to lignin content. The increase in recalcitrant compounds, which also includes later stages of decomposition, and N-poor litter may increase CO2 evolution, leading to low microbial carbon use efficiency. Likewise, it can also reduce the enzymatic activity of beta-glucosidase, Urease, and Phosphatase (Almagro et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Meanwhile, mineral fertilizer is linked to a higher number of microbes, which also had the same effect on the diversity (Table\u0026nbsp;9).\u003c/p\u003e\u003cp\u003eDehydrogenase is one of the few enzymes that are intracellular and present in viable cells and indicate microbial enzyme production (Dick \u0026amp; Kandeler, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Besides this, the availability of biomass is a determinant factor in the rate of decomposition of residue, which is again reflected in the soil enzymatic activity. The Nitrogen availability in the soil through mineral fertilizer and residue mixing (in Wheat based rotation) or compost and manure (in Lavender) could have increased the enzymatic activities in comparison to the unmanaged area (Almagro et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For instance, Kemp et al. (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) also found that the rate of decomposition of above-ground biomass, such as leaves is significantly faster in comparison to the below ground root litter. It indicates the role of the rooting system growth and structure and the presence of leaf litter in microbial utilization, which is reflected in the microbial respiration in soil.\u003c/p\u003e\u003cp\u003eAlthough the moisture content was higher, which we believe is due to the organic litter of perennial grasses and deciduous shrubs, due to the high diversity of above-ground biomass and low amount of simple carbon compounds in comparison to areas with manure and compost (Lavender Cultivation) and mineral fertilization, we found higher enzymatic activities under cultivated areas in comparison to unmanaged area. However, this diversity in the composition of litter also would be clear with the microbial community assessment.\u003c/p\u003e\u003cp\u003eOn the other hand, it is also possible that the heterogeneity of substrate that varies in its C: N stoichiometry may sustain the diverse microbial populations in smaller numbers, whereas the availability of nutrients under Lavender and wheat rotation areas may support larger proliferation and a number of narrow saprotrophic organisms. Another explanation could be that the organic matter decomposition takes place in phases where high-quality litter (with low C: N) decomposes quickly, releasing nutrients and increasing extracellular enzymatic activity, which is followed by the decomposition of low quality litter (high C: N, Lignin: N) (Liu et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This causes a shift in the number and abundance of microbial organisms in the community.\u003c/p\u003e\u003cdiv id=\"Sec38\" class=\"Section3\"\u003e\u003ch2\u003eColonies growth on media across different agricultural system\u003c/h2\u003e\u003cp\u003eWe cultured soil microbes in a number of different universal fungal, bacterial growth media, and specialized microbe growth media (Fig.\u0026nbsp;5). After 2 to 3 serial dilutions, we have presented the growth at a uniform dilution rate for all land management (Table\u0026nbsp;6). This conventional approach to studying the growth of microbes present in differing soil under enabling conditions, relies on morphological identification and is not representative due to numerous biases and hence is not reliable. Regardless, we continued with it to observe the growth and morphological growth of selective and general-purpose media.\u003c/p\u003e\u003cp\u003eA higher number of Actinomycetes was observed in Wheat based rotation and lavender, which indicates that the plant type has a significant effect on growth. The microbial population adapted to heterogenous (such as that of unmanaged land) may show some selective effect when cultivated on selective media (Vieira \u0026amp; Nahas, \u003cspan citationid=\"CR138\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Hence, we observed a lower number of CFUs in unmanaged areas with organic litter, which might have been sustaining k strategists which did not proliferate in nutrient-rich media.\u003c/p\u003e\u003cp\u003eThe effect of chemical fertilization was visible in our colony growth study. Generally, a higher number of colony growth was observed in the Wheat-based rotation, which is likely due to the adaptive ability of the saprotrophic population. The selective and general purpose media are rich in nutrients that allow easy proliferation of r strategists. Belay et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) also found a higher bacterial population under nitrogen fertilization. In addition, the colony's growth is influenced by temperature and media, which has influenced the growth of microorganisms (Viera \u0026amp; Nahas, 2005). In long-term fertilization, especially with Nitrogen and Fertilizer availability, the CFU growth of the bacterial population in artificial media is higher, which could have been through the survival of microbes that has a better mechanism of nutrient utilization. Moreover, this may also lead to a less diverse microbial growth at a higher number (He et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec39\" class=\"Section2\"\u003e\u003ch2\u003eMetagenomic Characterization across agricultural system\u003c/h2\u003e\u003cp\u003eOur findings suggest that land management practices influence the genetic composition of the microbial community in soil, allowing the proliferation and dominance of distinct microbial taxa. This may be through selection pressure or conducting conditions (Wang et al., \u003cspan citationid=\"CR143\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As a result, our observations of varied microbial taxa in cultivated soil (lavender cultivation and wheat-based rotation) suggest that regular and additive nutrient supply, along with multiple other factors, contributes to increased bacterial diversity in the soil. Meanwhile, decreased diversity in unmanaged soils indicated the survival of fewer and less diverse microbes with distinct life strategies (Osborn et al., 2024; Chen et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe differences in GC (S1; Table\u0026nbsp;5) may indicate a reflection of the GC-rich genome between the land management systems. For instance, the presence of phyla such as Actinobacteria in abundance may be present in long-term or perennial cropping systems (Delgado-Baquerizo et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Likewise, we observed a high total base count, which could mean a diverse microbial community in wheat-based rotation that may be metabolically diverse. Nonetheless, we found a higher total base count across the three land management systems, which shows that the microbial community between these systems have comparable community structures. The higher base number in both lavender and wheat-based systems is likely due to the presence of plant community under a fertilization regime that increases the microbial richness and functional potential with additive benefits associated with rhizodeposition (Xiao et al., \u003cspan citationid=\"CR146\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Berendsen et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOverall, our study found a pronounced shift in the microbial community that is primarily mediated through management practices. For instance, under lavender cultivation, a perennial crop harboured a high population of Actinobacteriota and Acidobacteriota. This was expected as the land had been amended with compost and manure as well as since organic matter addition has been associated with a higher population of Actinobacteria, Firmicutes, Chloroflexi and other enzymatic activities (Wang et al., \u003cspan citationid=\"CR143\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Our findings in Lavender cultivation with organic amendments are in line with this finding as well.\u003c/p\u003e\u003cp\u003eIn contrast, unmanaged soil, which contained a collection of wild grasses and leaves, harboured a remarkedly low Actinobacteriota population in this case. Here, taxonomic assessment of phyla revealed that the Proteobacteria phylum dominated the microbial community in abundance (Fig.\u0026nbsp;8). However, under this phyla, between Alphaproteobacteria and Gammaproteobacteria, the latter (40.94%) dominated in unmanaged soil. These Alphaproteobacteria are known to be involved in organic matter decomposition, and they are abundant in forest soil (Kim et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In the two cultivated soils, Proteobacteria did not overwhelmingly dominate, and both Alphaproteobacteria and Gammaproteobacteria were evenly distributed farther down the taxonomy. It further strengthens the argument that regular organic amendments help maintain a larger and more diversified microbial community positively associated with carbon cycling.\u003c/p\u003e\u003cp\u003eThe increasing abundance of orders like Vicinamibacterales and Gaiellales indicates the preferential colonization and proliferation in nutrient-rich areas. These orders were common in Lavender cultivation and wheat-based rotation but were lower in unmanaged land. These findings demonstrate the strong influence of plant species on the rhizosphere and bulk microbial community composition at the order level, with the land management system influencing the distribution of bacteria and supporting a distinct subset of bacterial taxa.\u003c/p\u003e\u003cp\u003eThe higher relative abundance of \u0026lsquo;others\u0026rsquo; among genera-based assessment in Wheat based rotation (more than 82%) and Lavender cultivation (more than 85%), in contrast to the unmanaged soil, with others occupying over 57%, indicates that the managed soils have highly diverse and complex microbial structure. Here, as evidenced by Alpha diversity, the diversity indices are extensively higher in soil with regular application of organic and mineral fertilization. The observed features across the three land and their similarity and dissimilarity also explain that planting biomass and no-tillage and the addition of organic matter enhances microbial diversity. Likewise, crop rotation and nutrient availability are positively linked to higher OTUs in soil. This was reflected in the low similarity of OTUs observed in unmanaged sites to that of both cultivated soils.\u003c/p\u003e\u003cp\u003eIn the case of organic amendments, organic carbon in compost-amended soils shows a pronounced effect on the microbial biomass and the microbial community. Saprophytic organisms are dependent on organic carbon-rich compounds for their growth and metabolism (Lupwayi et al., \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This is similar to our findings of a higher abundance of Actinobacteriota (34.2%) in Lavender cultivation. Here, compost and manure were added regularly, resulting in a much more diverse microbial community, which is in contrast to the lower proportion of Actinobacteriota and Acidobacteriota in unmanaged soil. This was similar in both of the cultivated soils where Actinobacteriota and Acidobacteriota, primarily involved in decomposition, were abundant. Acidobacteria are associated with resilience to acidic conditions (Philippot et al., \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2013\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eSimilarly, the heat map further indicated the association between the land management systems and the microbial taxa. Here, what showcases the complex action and mechanism associated with cultivated areas are the ecological niches that harbour much higher bacterial phyla numbers than unmanaged soil. Among the top 30 abundant genera, these genera comprise 54.74% of the total observed genus in unmanaged soil. In contrast, the most abundant 30 genera only comprise 22.68% (Lavender cultivation) and (slightly higher) 29.98% in Wheat based rotation. One other aspect in litter rich areas is concerned with its role in reducing nitrogen availability. Losses through NO3\u003csup\u003e\u0026minus;\u003c/sup\u003e leaching, gaseous release of N2 is linked with quality and amount of litter presence (Mart\u0026iacute;nez-Garc\u0026iacute;a et al., \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lyu et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Higher N cycle-related metabolism, including nitrite respiration, nitrate, and nitrite ammonification, was likewise linked to our function potential prediction in unmanaged soil (Fig.\u0026nbsp;17). This also demonstrates the effect that soil management and litter have on the nitrogen cycling process.\u003c/p\u003e\u003cp\u003eA generally higher presence of genera from Phyla Proteobacteria and Bacteroidata was observed from the phylogenetic tree (Fig.\u0026nbsp;19). However, we found higher diversity across all land management systems at the species level. There was a higher abundance of \u003cem\u003eLysobacter sp.\u003c/em\u003e, \u003cem\u003eAdhaeribacter terrae\u003c/em\u003e, \u003cem\u003eCaenimonas sp\u003c/em\u003e., and \u003cem\u003eSolitalea koreensis\u003c/em\u003e in uncultivated areas. Strains of Lysobacter are known to have pathogen suppression and extracellular enzyme production, with Caenimonas reported in unamended soils and present under stress (Rodr\u0026iacute;guez-Berbel et al., \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Gomez Exp\u0026oacute;sito et al., 2015). Meanwhile, species like \u003cem\u003eNitrospira japonica\u003c/em\u003e, Gemmatimonadetes, and Actinobacterium (WWH12) were higher in cultivated areas. Gemmatimonadetes are associated with anoxygenic photosynthesis, which has been reported in terrestrial and aquatic systems (Mujakić et al., \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Species from Actinobacteria are significant due to their role in carbon cycling, extracellular hydrolytic enzyme production, and organic matter degradation (Zhang et al., \u003cspan citationid=\"CR149\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Nitrospira is associated with the Nitrite-oxidizing mechanism and is a key factor in nitrogen cycling (Daims et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Gemmatimonadetes may also have slow growth and be helpful in long-term stability (Zeng et al., 2015). These are reported to be ubiquitous, with positive roles in vegetation restoration, disturbed soils, and areas rich in nutrients. Their slower growth rate indicates a link to their resilience to stress and play a stable role as k-strategists (Mujakić et al., \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe root structure, its significant role in carbon exudation, and the growth cycle in wheat-based rotation and lavender may also have been involved in the microbiome shift compared to unmanaged soil. Hence, mixed cropping is crucial to bacterial and fungal biomass due to its role in prompting enzymatic activity through exudation. Although plant species solely are not highly influential in microbial communities since they may not change the proportion of dominant taxa but may increase the relative proportion of rare species (Zhang et al., \u003cspan citationid=\"CR148\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This also sheds light on the dynamic complexities of the microbial community and the influence of multiple factors. Apart from that, the dominance of Gammaproteobacteria and Bacteroides has been associated with fresh litter presence and its decomposition, which has a positive role in carbon mineralization (Fierer et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Based on our observation, the higher labile organic matter and grass root exudates can help proliferate but result in lower taxa distribution under nutrient-limited conditions.\u003c/p\u003e\u003cdiv id=\"Sec40\" class=\"Section3\"\u003e\u003ch2\u003eMicrobial community and Diversity and its structuring based on differing Management systems\u003c/h2\u003e\u003cp\u003eThe alpha diversity analysis revealed clear differences in bacterial community structure under differing land management practices between rhizosphere-associated cultivated soils and unmanaged land. The Lavender cultivation and wheat-based rotation exhibited significantly higher species richness and diversity than the unmanaged area, which is reflected by the Chao1, observed features, Shannon, and Simpson indices. The increased Chao1 richness in both cultivated soils is likely due to the root-associated environments that provide a conducing and broader range of ecological niches and substrates, supporting a more diverse microbial community. This is also aided by the regular application of nutrients through organic amendments and mineral fertilizers. Root exudates, composed of sugars, amino acids, organic acids, and secondary metabolites, stimulate microbial proliferation and recruitment (Berendsen et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Bulgarelli et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The notably higher richness in the wheat and lavender rhizospheres compared to bulk soil aligns with previous findings that plant roots serve as microbial hotspots in the soil matrix (Mendes et al., \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, the influence of the rhizosphere effect may be reduced depending on the site-specific and biomass in the environment.\u003c/p\u003e\u003cp\u003eBased on alpha diversity indices, we found that management practices in Lavender and wheat cultivation can promote higher bacterial richness, diversity, and evenness in the soil microbial community. These results indicate that plant presence and identity modulate not only microbial community composition but also their ecological functional potential, with implications for nutrient cycling, soil health, and bioremediation.\u003c/p\u003e\u003cp\u003eOur findings of higher Xanthomonadales in unmanaged areas indicate the abundance of decomposers due to their role in forest litter decomposition. These bacterial orders are also linked with the possible association with Nitrate mineralization in soil (Kim et al., 2019). Sul et al. (2019) found that bacterial richness is higher in managed agricultural land than in unmanaged plots with grass. In some amendments, like charcoal, the management practices have an edge over the influence of the microbial community (Hardy et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The involvement of management practices creates a difference in cultivated land where limiting nutrients are addressed with multiple other practices. This contrasting difference exhibits the scenario between cultivated and unmanaged soil. The FAPROTAX analysis also provided insights into the status of uncultivated soil. The functions associated with hydrocarbon and aromatic compound degradation were substantially present. They may also explain the dominance of native soil taxa adapted to degrading organic residue and organic compounds in soil.\u003c/p\u003e\u003cp\u003eSimilarly, Phylum Firmicutes and genus Bacillus were highly abundant in Wheat based rotation. It could be the role of higher nutrient availability and its beneficial effect in cultivated soils. For instance, we also observed the genus Nitrospira in Wheat based rotation, which is associated with a positive role in Nitrite oxidation and hence plays a substantive role in Nitrogen cycling (Gu et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Fierer et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). The functional potential indicated that the microbial functioning related to Nitrate reduction and denitrification were higher in Wheat based rotation. We found that Taxa such as Chitinophagales and Pyrinomonadales were abundant under the conducive environment of Wheat-based rotation and are involved in the breakdown of complex compounds such as chitin (Chen et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and aid in carbon mineralization. Hence, these taxa were present in unmanaged areas, which explains its role in litter decomposition. Moreover, the availability of Nitrogen is another driving factor in shaping bacterial communities. Excessive fertilization is reported to have a negative effect on the bacterial community (Chen et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Hence, monitoring the reflection of management on microbial diversity, in the long run, will be crucial to improve microbial health.\u003c/p\u003e\u003cp\u003eThe Chao1 index reflected the wider niche provided by the cropping system, the plant biomass and nutrient availability that can support a diverse microbial community. Contrastingly, unmanaged areas exhibited lower diversity and higher dominance, suggesting fewer competitive or specialized taxa without rhizosphere influences. Based on our observation, a crucial aspect is the biomass density, the type of biomass. A number of studies have indicated that undisturbed ecosystems may entertain a distinctly differing microbial community (Buresova et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) that is driven by physiochemical parameters, amount and type of litter. In our case, we had wild growth but sparse, but still, we observed differences in Chloroflexim, Firmicutes, and Gemmatimonadota (higher proportional abundance in cultivated areas) between the differing management systems.\u003c/p\u003e\u003cp\u003eThe beta diversity analysis revealed clear shifts in microbial community composition between the differing land management systems. We found higher UniFrac distances, which explained the dissimilarity between lavender cultivation and Wheat-based rotation in uncultivated soil. This reflects the strong influence of root exudates in shaping distinct microbial communities, consistent with previous findings (Berendsen et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Bulgarelli et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, we also found a lower dissimilarity between lavender cultivation and Wheat-based rotation, which suggests a certain overlap in observed taxa, likely reflecting shared functional groups involved in nutrient cycling or root colonization. These results support the concept that plant species act as key drivers of rhizosphere microbiome differentiation, impacting community structure and phylogenetic diversity.\u003c/p\u003e\u003cp\u003eRegarding disease incidence, we found that taxa like Gaiella and Bacillus in cultivated soil, which is promising. These genera have been associated with areas of low disease incidence, indicating their positive metabolism in pathogen suppression (Babinska-Wensierska et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). More likely, we found a high amount of Thermoleophilia (16.48%) in a lavender field. Hence, their distribution has played a positive role since the relative incidence in unmanaged soil is lower. Beneficial genera like Bacillus are widely used as PGPR-promoting organisms, biofertilizers that promote nutrient availability through metabolite production and also suppress diseases through antagonism (Babinska-Wensierska et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Saxena et al., \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eActinobacteria and Firmicutes are involved in the breakdown of recalcitrant and complex organic compounds, which were present and in line with their increased abundance in Wheat based rotation and Lavender cultivation (Verzeaux et al., \u003cspan citationid=\"CR137\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The presence of biomass, the ecological niche for microbe proliferation and the addition of manure and fertilizer can increase the diversity of decomposers. Wang et al. (\u003cspan citationid=\"CR143\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) also found that long-term crops provide resources for supporting the proliferation of Actinobacteria and Firmicutes.\u003c/p\u003e\u003cp\u003eOne crucial aspect is the higher abundance of Acidobacteria in both Wheat based rotation and Lavender cultivation. These phyla are considered k strategists that exhibit slower growth rate and do not proliferate rapidly with substrate availability (Philippot et al., \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Hence, it might be one reason for the lower contribution to basal respiration in cultivated soil and higher CO2 production in uncultivated soil (Fig.\u0026nbsp;6). Besides, Acidobacteria occupied lower abundance in uncultivated soil, and instead, we observed a higher proportion of Proteobacteria and Bacteroidetes, which are r-strategists with lower substrate use efficiency. Moreover, the dominance of Gammaproteobacteria under Proteobacteria in uncultivated areas indicates the relationship with substrate litter since these are primary decomposers (Buresova et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Fierer et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eVicinamibacteria are oligotrophs involved in the solubilization of inorganic phosphorus through enzyme production that mediates P mineralization and have shown stress resilience (Boutsika et al., 2024). We found a high relative abundance of this class belonging to Acidobacteroita in lavender cultivation and Wheat based rotation, showing that the planting system had the positive benefit of allowing higher proliferation. This proliferation of bacterial groups and Phosphorus availability is mediated by \u003cem\u003egcd\u003c/em\u003e genes that, through multiple pathways, increase its availability under disturbed soil (Liang et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This signifies that these bacteria increase under nutrient amendments as well. Since, studies have shown differing results in the increase and decrease of copiotrophic organism after fertilization (Dai et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, the role of the dynamic interaction with cropping patterns and planting systems could help maintain the diverse structure of bacterial communities.\u003c/p\u003e\u003cp\u003eBacteroidia, Gammaproteobacteria dominance makes up over 57% of the dominance in unmanaged soil. These are r-strategists linked with higher growth and utilization of polysaccharides and complex compounds, which relates positively to the presence of organic matter in unmanaged soils. However, it also elucidates the high fluctuation in the dominance of microbial groups. Surprisingly, we found that with nutrient supply, we found a balance between r strategists and k strategists, indicating the role of plants in mediating a balance of diverse bacterial communities. The alphaproteobacteria, Vicinamibacteria, and Actinobacteria, are oligotrophs that could lead to a microbial stability and resilient community that grows moderately with a positive role in nutrient cycling and is less sensitive to biotic and abiotic stress in the soil.\u003c/p\u003e\u003cp\u003eThe higher relative abundance of Acidobacteria in Lavender (20.11%) and wheat-based rotation (28.73%) and lower in uncultivated soil (12.96%) is also likely due to the substrate availability and substrate utilization ability of Oligotrophs. The higher presence indicates their ability to sustain microbial diversity since these thrive under low nutrient availability and do not dominate the community when nutrient availability is high (Dai et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The microbial breakdown of lower C: N ratio litter increases soil organic carbon and nitrogen content and also has a positive effect on the enzymatic activity (Xiao et al., \u003cspan citationid=\"CR145\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe presence of bacterial genera like Bacillus and Pseudomonas was evident in Wheat based rotation. It may be linked to having a positive effect on pathogen suppression through pathways such as biofilm formation and root colonization. These genera are supposed to positively interact around the root interface and create a protective barrier to pathogen proliferation (Tao et al., \u003cspan citationid=\"CR130\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bais et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, since the agricultural environment is such a dynamic and complex system, monitoring the effect of land management and cropping on microbial community structure is required. The sensitive response to any changes in agricultural land management practices enhances their value in detecting and monitoring shifts in soil property dynamics from management. Our study demonstrates that agricultural management practices, along with the cropping system, can influence and shape the soil microbial diversity, alpha diversity, beta diversity and the functional potential of the microbial taxa present in the soil.\u003c/p\u003e\u003cp\u003eThe difference between Lavender and Wheat based rotation was also observed. Firstly, a highly diverse phylum classification in Wheat-based rotation might be due to the change in plant biomass with rotation that allowed for a diverse source of organic carbon-rich compounds. Besides this, the availability of nutrients. In this context, biomass is crucial since even diversification with wheat cultivars has been shown to shift microbial community structure in the rhizosphere with a higher abundance of Actinobacteria, Bacteroidetes and Proteobacteria in tall wheat cultivars (Kavamura et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Sphingomonadales were higher in uncultivated areas and in Lavender Cultivation. We believe it is due to the association of these two land management practices with perennial presence, abundant complex compounds from biomass in uncultivated areas and compost in lavender cultivation. It has been reported that areas rich in the presence of recalcitrant litter and residue and areas with low nutrient availability have an association with the degradation of polycyclic aromatic hydrocarbons (PAHs) (Siddiqi et al., \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Jeys et al., 2002). Massilia, Pedobacter, and Pseudomonas are higher in unmanaged areas than both of the cultivated areas. Massilia are root colonizers and several species are involved in breakdown of chitin under nutrient stress (Faramarzi et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Beneficial strains of Pseudomonas, and Bacillus are reported to produce IAA, and secondary metabolites (Chen et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHence, the clear demarcation and a distinction in the microbial diversity shows that unmanaged areas have microbial community structure dominated by limited taxa which may be explained by the selection pressure and stress continuation that allows for a dominance of limited taxa. Likewise, observations of beneficial bacteria involved in complex compound breakdown indicates their well-functioning mechanism however, probability of low substrate use efficiency poses question on their effect on carbon stabilization. On the other hand, soil management practices and cropping changes allow for a diversity microbial community structure with relative and proportionate distribution of r-strategists and k-strategists in agricultural soil. Hence, Sustainable management choices in soil amendment and cropping systems are crucial in balancing the soil microbial community structure. We believe long term monitoring managed and unmanaged land, their properties would provide a broader understanding of land management effect in soil.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOur study was conducted to understand the influence of 3 different land management practices on soil parameters and microbial community structure. We found that the management practices are a key driver of shift in microbial community composition with higher diversity in well managed and cultivated soil, primarily through fertilization and root mediated conducive environment. Alpha diversity and beta diversity indices indicated the distinct differentiation of the microbial distribution pattern in a microbial community. Higher enzymatic activities, moderate pH were observed in cultivated soils. Moreover, clear differentiation of highly diverse phyla and reduced phyla diversity were observed in managed and unmanaged soil respectively. This indicates the interactive influence of above ground and below ground biomass with fertilization regime that promotes higher diversity of microbial community. Meanwhile, unmanaged soil may promote lower diversity in microbial community that might be due to the aboveground biomass, decomposition processes, selective pressure which limits the proliferation of higher microbial diversity and exhibits presence of higher dominance of limited taxa. Therefore, understanding the influence of land use and management practices through identification and assessment of biological components/indicators are critical for evaluating the impact and effectiveness of land management strategies and agricultural practices early. Hence studying the long term influence on microbial community and enzyme activity with provide deeper insights into the applicability of management practices in agricultural soil.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatement and Declaration\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAuthors Contribution\u003c/b\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKarun Adhikari\u003c/strong\u003e: Original Draft Preparation, Writing and Editing, Laboratory Analysis, Statistical analysis, Visualization\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMariana Petkova\u003c/strong\u003e: Writing -Editing Reviewing, Laboratory Analysis, Supervision\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sequencing data are available at NCBI Sequence Read Archive (SRA) under BioProject PRJNA1292883.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors did not receive any funding for conducting the research. Karun Adhikari was supported by the Erasmus Mundus Joint Masters scholarship Program.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAllison SD, Vitousek PM (2005) Responses of extracellular enzymes to simple and complex nutrient inputs. Soil Biol Biochem 37(5):937\u0026ndash;944. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.soilbio.2004.09.014\u003c/span\u003e\u003cspan address=\"10.1016/j.soilbio.2004.09.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlmagro M, Ruiz-Navarro A, D\u0026iacute;az-Pereira E, Albaladejo J, Mart\u0026iacute;nez-Mena M (2021) Plant residue chemical quality modulates the soil microbial response related to decomposition and soil organic carbon and nitrogen stabilization in a rainfed Mediterranean agroecosystem. 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Environ Res Commun 6(7):075011. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1088/2515-7620/ad5b3e\u003c/span\u003e\u003cspan address=\"10.1088/2515-7620/ad5b3e\" 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":true,"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":"Land Management, Soil Enzyme, Relative Abundance, Microbial diversity","lastPublishedDoi":"10.21203/rs.3.rs-7730087/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7730087/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAims:\u003c/strong\u003e Land management practices are among the most crucial factors influencing soil properties. Integrated amplicon sequencing and biological properties analysis can provide contextual insights into how management practices shape soil microbial communities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We conducted a completely randomized sampling study at Agricultural University, Plovdiv, to assess the impact of Lavender Cultivation, Wheat-based Rotation and Unmanaged land, on soil microbial community structure and properties.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Taxonomic assessment indicated a clear distinction in microbial community composition. Unmanaged soils were dominated by reduced and less diverse but dominant microbial groups, possibly driven by selection pressure from limited resources. In contrast, cultivated soil supported diverse microbial community of r and k strategists. Enzymatic activity increased significantly (p≤0.05) in managed soil. Land management significantly influenced the pH, EC, Basal Respiration, and Soil Moisture content (p≤0.05). Higher soil respiration (CO2) was observed in uncultivated soil, indicating role of substrate quality in microbial substrate utilization efficiency. Proteobacteria (54.75%) was the dominant phyla in unmanaged land, followed by Bacteroidota (16.45%). In Lavender cultivation, Actinobacteriota (34.20%), Proteobacteria (20.56%), and Acidobacteriota (20.11%) were the most abundant. Similarly, in Wheat based rotation, diverse proportion of Acidobacteriota (28.73%), Actinobacteriota (19.97%), Proteobacteria (17.5%) and Bacteroidota (10.64%) was observed. Alpha diversity indices such as Shannon and Simpson index was higher in cultivated soil. Beta diversity analysis showed a distinct dissimilarity between uncultivated and cultivated soil.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Our findings indicate that interaction between factors such as cropping system, fertilization, and moisture content, distinctly shape the microbial community. Long term monitoring would help understand sustained effect on soil health.\u003c/p\u003e","manuscriptTitle":"Agricultural Land Management practices and their influence on microbial community composition and biological activity in soil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-30 07:50:46","doi":"10.21203/rs.3.rs-7730087/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":"484f3b2b-f623-4ad9-898f-5eb24d01e5ae","owner":[],"postedDate":"September 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-07T06:36:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-30 07:50:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7730087","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7730087","identity":"rs-7730087","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}