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Microbial ecologists have made exceptional improvements in our understanding of microbiomes in the last decade due to breakthroughs in sequencing technologies. These advances have wide-ranging implications for fields ranging from agriculture to human health. Due to limitations in databases, the majority of microbial ecology studies use a binning approach to approximate taxonomy based on DNA sequence similarity. There remains extensive debate on the best way to bin and approximate this taxonomy. Here we examine two popular approaches using a large field-based data set examining both bacteria and fungi and conclude that there are not major differences in the ecological outcomes. Thus, it appears that standard microbial community analyses are not overly sensitive to the particulars of binning approaches. Recent discussion focuses on the best method for delineating microbial taxa, based on either exact sequence variants (ESVs) or traditional operational taxonomic units (OTUs) of marker gene sequences. We sought to test if the binning approach (ESVs versus 97% OTUs) affected the ecological conclusions of a large field study. The data set included sequences targeting all bacteria (16S rRNA) and fungi (internal transcribed spacer [ITS]), across multiple environments diverging markedly in abiotic conditions, over three collection times. Despite quantitative differences in microbial richness, we found that all α and β diversity metrics were highly positively correlated ( r > 0.90) between samples analyzed with both approaches. Moreover, the community composition of the dominant taxa did not vary between approaches. Consequently, statistical inferences were nearly indistinguishable. Furthermore, ESVs only moderately increased the genetic resolution of fungal and bacterial diversity (1.3 and 2.1 times OTU richness, respectively). We conclude that for broadscale (e.g., all bacteria or all fungi) α and β diversity analyses, ESV or OTU methods will often reveal similar ecological results. Thus, while there are good reasons to employ ESVs, we need not question the validity of results based on OTUs. IMPORTANCE Microbial ecologists have made exceptional improvements in our understanding of microbiomes in the last decade due to breakthroughs in sequencing technologies. These advances have wide-ranging implications for fields ranging from agriculture to human health. Due to limitations in databases, the majority of microbial ecology studies use a binning approach to approximate taxonomy based on DNA sequence similarity. There remains extensive debate on the best way to bin and approximate this taxonomy. Here we examine two popular approaches using a large field-based data set examining both bacteria and fungi and conclude that there are not major differences in the ecological outcomes. Thus, it appears that standard microbial community analyses are not overly sensitive to the particulars of binning approaches.

The phylogenetic depth at which arbuscular mycorrhizal (AM) fungi harbor a coherent ecological niche is unknown, which has consequences for operational taxonomic unit (OTU) delineation from sequence data and the study of their biogeography. We tested how changes in AM fungi community composition across habitats (beta diversity) vary with OTU phylogenetic resolution. We inferred exact sequence variants (ESVs) to resolve phylotypes at resolutions finer than provided by traditional sequence clustering and analyzed beta diversity profiles up to order-level sequence clusters. At the ESV level, we detected the environmental predictors revealed with traditional OTUs or at higher genetic distances. However, the correlation between environmental predictors and community turnover steeply increased at a genetic distance of c. 0.03 substitutions per site. Furthermore, we observed a turnover of either closely or distantly related taxa (respectively at or above 0.03 substitutions per site) along different environmental gradients. This study suggests that different axes of AM fungal ecological niche are conserved at different phylogenetic depths. Delineating AM fungal phylotypes using DNA sequences should screen different phylogenetic resolutions to better elucidate the factors that shape communities and predict the fate of AM symbioses in a changing environment.

To preserve wetland ecosystem function, federal and state agencies have developed assessment procedures to better manage remaining wetland areas. Currently, wetland assessments do not consider microorganisms when determining wetland quality. This is notable, because fungi are often the primary decomposers of organic material and thus important players in nutrient cycling. The objective of this study is to quantify how wetland quality, as measured using the Ohio Rapid Assessment Method (ORAM), relates to fungal community composition. We sampled soils from six depressional emergent marshes in Ohio belonging to each of the three ORAM quality categories, assessed soil physicochemical properties, and recovered fungal DNA. We then determined if wetland quality as expressed by the ORAM reflects soil health. Our results indicate that ORAM scoring methodology significantly explains differences in fungal community composition between wetlands. We also found that soil physicochemical properties not currently included in the ORAM are strong drivers of fungal community composition, particularly bulk density, pH, soil organic matter, and soil moisture. Overall, our results suggest fungal community composition reflects wetland quality as assessed by the ORAM, and that the ORAM and potentially other wetland assessments could better capture the soil environment by including easily measured soil physicochemical properties.