Multiscale responses of microbial life to spatial distance and environmental heterogeneity in a patchy ecosystem

Abstract

Spatial distance (SD) and environmental heterogeneity (EH) are currently thought to represent major factors shaping genetic variation and population abundance, but their relative importance is still poorly understood. Because EH varies at multiple spatial scales, so too are microbial variables expected to vary. The determination of SD ؋ EH interactions at multiple scales is, however, not a trivial exercise, especially when one examines their effects on microbial abundance and genomic similarities. Here we assessed those interactions at all scales perceptible in a patchy environment composed of known plant species and of heterogeneous soil physical and chemical parameters. For free-living, soil-borne Burkholderia ambifaria, genomic similarities responded to most of the spatial scales that the experimental sampling scheme could reveal, despite limited dispersal of the individuals. Species abundance and community composition were, however, responding to much smaller scales more consistent with local responses to EH. Our results suggest that whole-genome similarities may reflect the simultaneous effects of both SD and EH in microbial populations, but the pure effects of each factor only contributed to <2% of the total genetic variation. The large amount of unexplained variation that remains after considering most environmental, spatial, and biological interactions is then posited to be the result of noise introduced by unmeasured environmental and spatial variability, sampling effects, and neutral ecological drift.biogeography ͉ Burkholderia ͉ multivariate analysis ͉ rhizosphere ͉ spatial modeling

Turnover of soil bacterial diversity driven by wide-scale environmental heterogeneity

“…Nevertheless, this metric was compared with the average similarity at different scales. Here, w 16 and E d16 were 0.65 and 0.84, respectively, representing higher values than the average similarities calculated at different scales.…”

“…Here the objective was to determine if bacterial similarity was determined by the similarity of habitat at a local spatial scale (16 km) and at the patch scale, that is, if similar habitats house similar bacterial communities. The confrontation of initial similarities (w 16 and E d16 , Fig. 4a) exhibited a relationship modelled with a linear regression type II model.…”

“…Nowadays, TAR is commonly used in this form in most microbial biogeographical studies 3,9,[14][15][16] to assess microbial diversification and its potential relative dependency on ''dispersal'' and ''habitat heterogeneity'' (including habitat diversity and landscape configuration) 4 . Nevertheless, the TAR is still highly debated, particularly regarding its form, underlying hypotheses and factors affecting the relationship [17][18][19] .…”

“…Variations in microbial community between soils were assessed by bacterial Automated Ribosomal RNA Intergenic Spacer Analysis (ARISA) directly on soil DNA 25 . The TAR was then applied to ARISA data by considering the slope (z bacteria ) together with the initial similarity 5 (w 16 ) at the grain size of the study (16 km) and the average similarity ðwÞ as proposed by Morlon et al 4 to complete the analysis of community spatial variations. In parallel, soil habitat, namely the ''description of a physical place, at a particular scale of space and time, where an organism either actually or potentially lives'' 26 , was characterized by including pedoclimatic, geomorphologic and land-use data.…”

Biogeography of bacterial communities in hot springs: a focus on the actinobacteria

“…showed Zambia and Kenya hot springs (less distant sites) having a more similar actinobacterial community structure (Online Resource 2). Taken together, these findings, and those from Song et al [49], indicate that the differences in actinobacterial community composition in hot springs are a function of both environmental heterogeneity and geographic distance [32,33,42].…”