Soil microbial community responses to multiple experimental climate change drivers

Abstract

Researchers agree that climate change factors such as rising atmospheric [CO2] and warming will likely interact to modify ecosystem properties and processes. However, the response of the microbial communities that regulate ecosystem processes is less predictable. We measured the direct and interactive effects of climatic change on soil fungal and bacterial communities (abundance and composition) in a multifactor climate change experiment that exposed a constructed old-field ecosystem to different atmospheric CO2 concentration (ambient, +300 ppm), temperature (ambient, +3 degrees C), and precipitation (wet and dry) might interact to alter soil bacterial and fungal abundance and community structure in an old-field ecosystem. We found that (i) fungal abundance increased in warmed treatments; (ii) bacterial abundance increased in warmed plots with elevated atmospheric [CO2] but decreased in warmed plots under ambient atmospheric [CO2]; (iii) the phylogenetic distribution of bacterial and fungal clones and their relative abundance varied among treatments, as indicated by changes in 16S rRNA and 28S rRNA genes; (iv) changes in precipitation altered the relative abundance of Proteobacteria and Acidobacteria, where Acidobacteria decreased with a concomitant increase in the Proteobacteria in wet relative to dry treatments; and (v) changes in precipitation altered fungal community composition, primarily through lineage specific changes within a recently discovered group known as soil clone group I. Taken together, our results indicate that climate change drivers and their interactions may cause changes in bacterial and fungal overall abundance; however, changes in precipitation tended to have a much greater effect on the community composition. These results illustrate the potential for complex community changes in terrestrial ecosystems under climate change scenarios that alter multiple factors simultaneously.

FIG. 1.

PCoA analysis based on Unifrac of clone libraries (A) and UniFrac cluster analysis (B) for bacterial soil communities. Acidobacterial and fungal soil communities exhibited similar patterns (data not shown). Unifrac Jackknife supports for each node of the Unifrac cluster analysis are indicated (1,000 permutations). White and black symbols represent dry and wet plots, respectively. Dashed and solid lines were drawn to highlight dry and wet treatments, respectively. Diamonds represent aCO₂aTemp treatments, squares represent eCO₂aTemp treatments, circles represent aCO₂eTemp treatments, and triangles represent eCO₂eTemp treatments.

FIG. 2.

Relative abundance of bacterial phyla within samples originating from wet plots (A) and dry plots (B). Phylogenetic affiliations of clones are based on 16S rRNA gene sequences assigned through the Classifier program within the Ribosomal Database Project.

FIG. 3.

Fungal rRNA neighbor-joining tree of SCGI clones and distribution of different subclades recovered from each treatment for wet plots. Scale bars represent 2% changes. Numbers at the nodes represent bootstrap resampling support based on 100 replicates; only values >50 are presented.