Assessment of structure and function of soil bacterial communties along land use and mangement gradients in the Biodiversity Exploratories


Scientific investigators:

Prof. Dr. Rolf Daniel

(University Göttingen)

 

Goals

 - Analysis of large-scale changes in soil bacterial community composition and diversity associated with different land use and management types.

- Investigation of small-scale biogeographical effects on soil bacterial community composition and diversity (Part of the SCALEMIC experiment).

- Assessment of the influence of tree species on structure, diversity and function of soil microbial communities.

- Identification of differences in microbial key functions typical for the land use and management types or Biodiversity Exploratories.

Hypotheses

 - Land use and management type have a significant large-scale impact on soil bacterial community composition and diversity by influencing soil properties.

- The overall community composition of soil bacterial communities with respect to the presence of dominant phylogenetic groups are almost unaffected by small-scale biogeographical effects, but the abundance of the different groups will change with respect to the different sampling periods.

- Phylogenetic and functional profiles of soil bacterial communities associated to oak and beech are more similar than those derived from spruce, as oak and beech are deciduous trees and both belong to the family Fagaceae.

- Key functions presenting differential distribution between the different land use types and management types at one exploratory are also relevant within the other exploratories.

 

Methods

- Extraction of total DNA and RNA from selected soil samples.

- Phylogenetic analysis of bacterial communities by bar-coded amplicon pyrosequencing of partial 16S rRNA genes.

- To investigate microbial activities in soil, microbial gene expression is analyzed by a metatranscriptomic approach: enriched mRNA is converted to cDNA which is subsequently subjected to pyrosequencing. 

- All pyrosequencing-derived data is analyzed by applying bioinformatical tools. The impacts of land use type, management type, tree species and soil characteristics on structure, diversity and function of soil microbial communities are investigated by statistical analyses.