Microbial diversity: A spatial study of microbial community assemblages in the Floridian Aquifer

Background/Question/Methods

As urbanization continues, agencies at all levels must have a way to assess the health of an ecosystem and microbial diversity is one fraction of ecosystem diversity that demands greater attention due to the sensitivity of microbes to their environment. Past studies have elucidated the importance of microbial assemblages, but few studies have looked at regional scales to evaluate how environmental conditions could affect the community assembly. This study examines the Floridian Aquifer to evaluate conditions (light, redox potential, anions, dissolved oxygen (DO), pH, alkalinity) that may play significant roles in affecting microbial communities. 13 sites were chosen, 3 in North Florida and 10 in Central Florida, to compare environments to molecular fingerprints using 16S phylogeny and Terminal Restriction Fragment Length Polymorphism (T-RFLP) techniques. Multiple stations were designated at 7 sites to measure effects of depth and distance from the cave opening. Physicochemical water measurements (water sample, temperature, pH, light availability, flow) were collected in conjunction with microbial mat samples.

Results/Conclusions

Microbial assemblages varied throughout the region of the Floridian aquifer. Using multivariate analyses, patterns emerge demonstrating conditions, such as redox and light, have significant affects on the microbial communities (ANOSIM, Bonferroni-corrected p-value = 0.001). Further non-parametric analyses reveal that sites in northern Florida are significantly different from Southern Florida sites (ANOSIM, Bonferroni-corrected p-value < 0.01). Also, multivariate analyses NMDS (Non-Parametric Multidimensional Scaling) and CCA (Canonical Correspondence Analysis) demonstrate underlying interactions that may be the cause for differences seen at sites. CCA plots express the effect variables on a gradient have on the microbial communities. Hence, in order to understand how microbes naturally interact with their environment, measures must be taken to evaluate each site as a separate entity. Increased knowledge about these sites enhances the ability to predict whether an area has contamination by the assemblies found in the ecosystem. By evaluation of microbial communities as a response to changes in environmental factors, we can increase the predictive powers policy makers have in decisions involving the ecosystems.