Assessing the Spatial Heterogeneity in Soil Microbial Populationss in Agroforestry Systems of Semiarid Central India
2025
Sovan Debnath | Sharwan Lal Yadav | Suresh Ramanan S. | Musineni Ashajyothi | Ashok Yadav | Asha Ram | Sushil Kumar | Naresh Kumar | Rajendra Prasad | Ayyanadar Arunachalam
Numbers and diversity of living microorganisms are rich in soil of agroforestry systems (AFS). However, study on their spatial heterogeneity between tree and intercrop rows is largely limited. In this context, a study was undertaken to elucidate the impact of tree and intercrop rows on spatial heterogeneity in culturable soil bacteria, fungi, and actinobacteria populationss and their relation with general soil properties. Topsoil (0–15 cm) and subsoil (15–30 cm) samples were collected in triplicates from tree (TRS) and intercrop (ICS) rows of a few predominant AFS [Indian gooseberry (IGB), Indian jujube (IJJ), Malabar neem (MN), and teak (TK)-based] of semiarid Central India along with a cropland (SCL) and evaluated for quantifiable soil microbial populations. IGB-based AFS registered highest populations of bacteria (133×105 and 103×105 CFU g soil–1) and fungi (16×104 and 11×104 CFU g soil–1) at both topsoil and subsoil of TRS, respectively. At ICS, IGB-based AFS again showed highest populations of bacteria (87×105 CFU g soil–1) at topsoil but fungi (4×104 CFU g soil–1) at subsoil. IJJ-based AFS registered the highest populations of actinobacteria in both TRS (16×103 and 13×103 CFU g soil–1) and ICS (12×103 and 7×103 CFU g soil–1) at topsoil and subsoil, respectively. Overall, IGB-based AFS increased the observed soil microbial populations most intensively, as indicated by statistics-based multiparametric indices. Fungal populations in soil revealed a strong and significant correlation with dehydrogenase activity (r= 0.84; P <0.0001), organic C (r= 0.82; P <0.0001), and available P (r= 0.77; P <0.001). We conclude that in view of spatial heterogeneity observed in a single microbial groups, integrated multiparametric indices may be used for a rational appraisal of combined microbial populations.
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