Local and Regional Scale Heterogeneity Drive Bacterial Community Diversity and Composition in a Polar Desert

Abstract

The distribution of organisms in an environment is neither uniform nor random but is instead spatially patterned. The factors that control this patterning are complex and the underlying mechanisms are poorly understood. Soil microbes are critical to ecosystem function but exhibit highly complex distributions and community dynamics due in large part to the scale-dependent effects of environmental heterogeneity. To better understand the impact of environmental heterogeneity on the distribution of soil microbes, we sequenced the 16S rRNA gene from bacterial communities in the microbe-dominated polar desert ecosystem of the McMurdo Dry Valleys (MDV), Antarctica. Significant differences in key edaphic variables and alpha diversity were observed among the three lake basins of the Taylor Valley (Kruskal-Wallis; pH: χ² = 68.89, P < 0.001, conductivity: χ² = 35.03, P < 0.001, observed species: χ² = 7.98, P = 0.019 and inverse Simpson: χ² = 18.52, P < 0.001) and each basin supported distinctive microbial communities (ANOSIM R = 0.466, P = 0.001, random forest ratio of 14.1). However, relationships between community structure and edaphic characteristics were highly variable and contextual, ranging in magnitude and direction across regional, basin, and local scales. Correlations among edaphic factors (pH and soil conductivity) and the relative abundance of specific phyla were most pronounced along local environmental gradients in the Lake Fryxell basin where Acidobacteria, Bacteroidetes, and Proteobacteria declined while Deinococcus-Thermus and Gemmatimonadetes increased with soil conductivity (all P < 0.1). Species richness was most strongly related to the soil conductivity gradient present within this study system. We suggest that the relative importance of pH versus soil conductivity in structuring microbial communities is related to the length of edaphic gradients and the spatial scale of sampling. These results highlight the importance of conducting studies over large ranges of key environmental gradients and across multiple spatial scales to assess the influence of environmental heterogeneity on the composition and diversity of microbial communities.

Keywords: 16S rRNA genes; McMurdo Dry Valleys; environmental heterogeneity; gradient analysis; polar desert; spatial scale.

FIGURE 1

Canonical correspondence analysis (CCA) of soil samples demonstrates that community composition differs both among and within basins and that the role of conductivity, distance to trough, and pH in driving within-basin variation differs among basins. Arrows indicate direction and magnitude of significant environmental factors affecting bacterial community structure.

FIGURE 2

Non-metric multidimensional scaling plots created using (A) Bray–Curtis and (B) Jaccard distances show distinctiveness of communities among basins.

FIGURE 3

Basin scale spatial variability of (A) pH, (B) conductivity, (C) alpha diversity (observed species), and (D) beta diversity (Jaccard distance) (mean ± standard error) along radial transects of polygons. Beta diversity was calculated by pooling samples from each distance from the trough within each lake basin.

FIGURE 4

Median relative abundance of top phyla within basins along polygon radial transects (filtered to minimum 1% average relative abundance).

FIGURE 5

Sliding window model: Relative contributions of pH and conductivity to explainable variation in observed species across (A) the pH gradient and (B) the conductivity gradient. Models reveals that EC is generally more influential to community diversity and composition, but when EC is low, pH is more important.

FIGURE 6

Assessing relative influence of edaphic factors over alpha diversity (top) and major phyla relative abundances (bottom) using Spearman rank correlations, revealing that phyla tend to respond in a similar direction regardless of basin. ^∗P ≤ 0.05, ^∗∗P ≤ 0.01, ^∗∗∗P ≤ 0.001. P-values of distance from trough, pH, and conductivity adjusted for multiple comparison using Benjamini and Hochberg (1995).