In urban environments, green roofs provide a number of benefits, including decreased urban heat island effects and reduced energy costs for buildings. However, little research has been done on the non-plant biota associated with green roofs, which likely affect their functionality. For the current study, we evaluated whether or not green roofs planted with two native plant communities in New York City functioned as habitats for soil fungal communities, and compared fungal communities in green roof growing media to soil microbial composition in five city parks, including Central Park and the High Line. Ten replicate roofs were sampled one year after planting; three of these roofs were more intensively sampled and compared to nearby city parks. Using Illumina sequencing of the fungal ITS region we found that green roofs supported a diverse fungal community, with numerous taxa belonging to fungal groups capable of surviving in disturbed and polluted habitats. Across roofs, there was significant biogeographical clustering of fungal communities, indicating that community assembly of roof microbes across the greater New York City area is locally variable. Green roof fungal communities were compositionally distinct from city parks and only 54% of the green roof taxa were also found in the park soils. Phospholipid fatty acid analysis revealed that park soils had greater microbial biomass and higher bacterial to fungal ratios than green roof substrates. City park soils were also more enriched with heavy metals, had lower pH, and lower quantities of total bases (Ca, K, and Mg) compared to green roof substrates. While fungal communities were compositionally distinct across green roofs, they did not differentiate by plant community. Together, these results suggest that fungi living in the growing medium of green roofs may be an underestimated component of these biotic systems functioning to support some of the valued ecological services of green roofs.

Most tropical rain forests contain diverse arrays of tree species that form arbuscular mycorrhizae. In contrast, the less common monodominant rain forests, in which one tree species comprises more than 50% of the canopy, frequently contain ectomycorrhizal (ECM) associates. In this study, I explored the potential for common ECM networks, created by aggregations of ECM trees, to enhance seedling survivorship near parent trees. I determined the benefit conferred by the common ECM network on seedling growth and survivorship of an ECM monodominant species in Guyana. Seedlings with access to an ECM network had greater growth (73% greater), leaf number (55% more), and survivorship (47% greater) than seedlings without such access, suggesting that the ECM network provides a survivorship advantage. A survey of wild seedlings showed positive distance‐dependent distribution and survival with respect to conspecific adults. These experimental and survey results suggest that the negative distance‐dependent mechanisms at the seedling stage thought to maintain tropical rain forest diversity are reversed for ECM seedlings, which experience positive feedbacks from the ECM network. These results may in part explain the local monodominance of an ECM tree species within the matrix of high‐diversity, tropical rain forest.

The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential ‘indicator’ taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.