Comparative Assessment of Soil Microbiome Across Land-Use Types and Depths

Thesis Abstract

Soil microbial communities underpin nutrient cycling and soil health, yet their composition and functional potential across diverse land-use types and soil depths remain inadequately characterized in many agricultural and natural systems. This study addresses the problem of limited understanding of how land-use transitions (agroecosystems, pastures, urban greenspaces, and natural forests) interact with soil depth to shape microbiome structure, diversity, and inferred function, with implications for ecosystem services and sustainable land management. The aim is to compare soil microbiomes across land-use types and depth horizons (0–10 cm, 10–20 cm, 20–40 cm) and to identify environmental drivers of observed patterns. Specific objectives are (i) to quantify taxonomic diversity and community composition of bacteria, fungi, and archaea across land-use types and depths using amplicon sequencing; (ii) to infer functional potential through shotgun metagenomics in a stratified subset of samples; (iii) to evaluate soil physico-chemical determinants (pH, organic carbon, moisture, nutrient status) as predictors of microbiome structure via multivariate analyses; (iv) to test for land-use and depth interaction effects on microbial networks and keystone taxa; and (v) to relate microbiome patterns to measured soil enzyme activities (?-glucosidase, urease, phosphatase) as proxies for ecosystem processes. The population comprises soils from five representative land-use types (annual cropland, perennial pasture, mixed-use urban greenspace, deciduous forest, and native woodland) within a temperate region. A stratified random sampling design will yield a total of 180 soil cores (30 cores per land-use type, across three depth horizons) collected in triplicate at six geographically dispersed farms and reserves to ensure comparability and generalizability. DNA will be extracted with a standardized protocol, and 16S rRNA gene and ITS region amplicons will be sequenced on the Illumina MiSeq platform for bacteria/archaea and fungi, respectively; a subset of samples (n=36) will undergo shallow whole-genome shotgun sequencing to augment functional inference. Quantitative PCR will quantify key microbial functional groups (nitrifiers, mycorrhizal fungi, and lignocellulose-degrading bacteria). Soil enzyme activities will be measured using colorimetric assays, and soil physicochemical properties will be characterized using standard soil analysis methods. Data analysis will proceed in several stages (i) sequence data will be processed with QIIME2, with amplicon sequence variants (ASVs) identified at 97% similarity for bacteria and fungi, and alpha and beta diversity metrics calculated; differential abundance will be assessed using DESeq2, controlling for false discovery rate. (ii) Multivariate ordination (PCoA, NMDS) and PERMANOVA will test for main effects of land-use type, depth, and their interaction on community composition; (iii) redundancy analysis (RDA) and canonical correspondence analysis (CCA) will relate microbial communities to soil properties; (iv) network inference (SparCC) will identify co-occurrence patterns and keystone taxa, with modularity analyses to detect habitat-specific network topology; (v) functional potential will be inferred from metagenomic data using MG-RAST or similar pipelines and cross-validated against enzyme activity measurements through regression analyses. The study expects higher microbial diversity and more complex networks in natural forests compared with urban greenspaces and croplands, with decreasing diversity and functional potential with depth, but potentially enriched saprotrophic fungi and archaea in deeper horizons of forest soils. Land-use–depth interactions are anticipated to significantly shape the balance of bacterial and fungal communities, and to influence soil enzyme activities through shifts in microbial functional guilds. The contribution to knowledge includes mechanistic insights into how land-use conversion and soil depth jointly govern microbial community structure, function, and ecosystem process proxies, informing land-management strategies to sustain soil health and productivity. The study will provide a validated framework for predicting microbiome-mediated soil processes in temperate landscapes and will identify keystone taxa and functional genes as potential indicators for monitoring and guiding remediation or conservation efforts. The main conclusion will articulate the relative importance of land-use type versus soil depth in shaping microbiomes and associated processes, with recommendations for land managers on practices (e.g., organic matter management, reduced disturbance, diversified cropping) to preserve microbial diversity and function across depth profiles.