Multivariate analysis of soils: microbial biomass, metabolic activity, and bacterial-community structure and their relationships with soil depth and type

• Published in: Journal of plant nutrition and soil science Vol. 174; no. 3; pp. 381 - 394
• Main Authors: Gelsomino, Antonio, Azzellino, Arianna
• Format: Journal Article
• Language: English
• Published: Weinheim WILEY-VCH Verlag 01.06.2011; WILEY‐VCH Verlag; Wiley-VCH
• Subjects: acid phosphatase; agricultural soils; Agronomy. Soil science and plant productions; algorithms; arylsulfatase; bacterial communities; Biochemistry and biology; Biological and medical sciences; Chemical, physicochemical, biochemical and biological properties; coniferous forests; data collection; denaturing gradient gel electrophoresis; depth gradients; DGGE community fingerprinting; discriminant analysis; DNA; energetic ecophysiological indices; enzyme activity; forest soils; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; grassland soils; ground cover plants; highlands; hydrolysis; land use; microbial biomass; Microbiology; multivariate analysis; multivariate statistics; organic soils; pedogenetic horizons; Physics, chemistry, biochemistry and biology of agricultural and forest soils; ribosomal RNA; ribotypes; silt; soil depth; soil enzymes; soil microorganisms; soil sampling; Soil science; Soil-plant relationships. Soil fertility; Soil-plant relationships. Soil fertility. Fertilization. Amendments; DGGE community fingerprinting; soil enzymes; Multivariate analysis; Depth; Bacteria; Microbial community; pedogenetic horizons; Community structure; Gradient; depth gradients; Gel electrophoresis; Enzyme; Biochemical compound; Denaturing gradient gel electrophoresis; Ecophysiology; Microbial biomass; Biological activity; Statistical method; Soils; Type; Fingerprint method; multivariate statistics; Prokaryote; energetic ecophysiological indices; Microorganism; Soil plant relation
• ISSN: 1436-8730; 1522-2624; 1522-2624
• DOI: 10.1002/jpln.200900267

A multivariate statistical approach based on a large data set of abiotic and biotic variables was used to classify four contrasting‐land‐use soils. Soil samples were collected at increasing depth from a calcareous agricultural soil, a temperate upland grassland soil, a moderately acidic agricultural soil, and an acidic pine forest soil. Analytical investigations were carried out by using a combination of conventional physical, chemical, and biochemical methods coupled with denaturing gradient gel electrophoresis (DGGE) community fingerprinting of PCR‐amplified 16S rRNA gene‐coding fragments from soil‐extracted total‐community DNA. The data set of soil physical, chemical, and biochemical variables was reduced in dimensionality by means of a principal‐component‐analysis (PCA) procedure. Compositional shifts in soil bacterial‐community structure were analyzed through a clustering algorithm that allowed identifying six main bacterial‐community clusters. DGGE fingerprinting clusters were further analyzed by discriminant analysis (DA) using extracted PCA components as explanatory variables. Soil organic matter–related pools (TOC, TN) and functionally related active pools (microbial biomass C and N, K2SO4‐extractable C) significantly decreased with soil depth, and resulted statistically linked to one other and positively related to enzymatic activities (acid phosphatase, arylsulfatase, β‐glucosidase, dehydrogenase, hydrolysis of fluorescein diacetate) and silt content. Besides organic‐C gradients, pedogenetic‐driven physico‐chemical properties, and possibly soil thermal and moisture regimes seemed to play a key role in regulating size and energetic ecophysiological status of soil microbial communities. DGGE analysis showed that contrasting horizons were conducive to the dominance of particular bacterial ribotypes. DA revealed that the bacterial‐community structure was mainly influenced by organic matter–related variables (TOC, TN, CEC, Cflush, Nflush, Extr‐C), chemical properties such as pH, CaCO3, and EC, together with textural properties. Results indicate that, beyond land use or plant cover, pedogenetic‐driven physico‐chemical conditions changing with soil type and depth are the key factors regulating microbial size and activity, and determining the genetic structure of bacterial community.