Seasonal Changes of Airborne Bacterial Communities Over Tokyo and Influence of Local Meteorology

Abstract There are many ecological diversity measures, but their suitability for use with highly diverse bacterial communities is unclear and seldom considered. We assessed a range of species richness and evenness/dominance indices, and the use of species abundance models using samples of bacteria from zinc-contaminated and control soils. Bacteria were assigned to operational taxonomic units (OTUs) using amplified ribosomal DNA restriction analysis of 236 clones from each soil. The reduced diversity apparent in the contaminated soil was reflected by the diversity indices to varying degrees. The number of clones analysed and the weighting given to rare vs. abundant OTUs are the most important considerations when selecting measures. Our preferences, arrived at using theory and practical experience, include: the log series index alpha; the Q statistic (but only if coverage is 50% or more); the Berger-Parker and Simpson's indices, although their ecological relevance may be limited; and, unexpectedly, the Shannon-Wiener and Shannon evenness indices, even though their meanings may not be clear and their values inaccurate when coverage is low. For extrapolation, the equation for the log series distribution seems the best for extrapolating from OTU accumulation curves while non-parametric methods, such as Chao 1, show promise for estimating total OTU richness. Due to a preponderance of single-occurrence OTUs, none of the five species abundance models fit the OTU abundance distribution of the control soil, but both the log and log normal models fit the less diverse contaminated soil. Species abundance models are useful, irrespective of coverage, because they address the whole distribution of a sample, aiding comparison by revealing overall trends as well as specific changes in particular abundance classes.

Considering the importance of its potential implications for human health, agricultural productivity, and ecosystem stability, surprisingly little is known regarding the composition or dynamics of the atmosphere's microbial inhabitants. Using a custom high-density DNA microarray, we detected and monitored bacterial populations in two U.S. cities over 17 weeks. These urban aerosols contained at least 1,800 diverse bacterial types, a richness approaching that of some soil bacterial communities. We also reveal the consistent presence of bacterial families with pathogenic members including environmental relatives of select agents of bioterrorism significance. Finally, using multivariate regression techniques, we demonstrate that temporal and meteorological influences can be stronger factors than location in shaping the biological composition of the air we breathe.