Soil microbiome predictability increases with spatial and taxonomic scale.

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States.

The National Ecological Observatory Network's soil metagenomes: assembly and basic analysis.

The largest dataset of soil metagenomes has recently been released by the National Ecological Observatory Network (NEON), which performs annual shotgun sequencing of soils at 47 sites across the United States. NEON serves as a valuable educational resource, thanks to its open data and programming tutorials, but there is currently no introductory tutorial for accessing and analyzing the soil shotgun metagenomic dataset. Here, we describe methods for processing raw soil metagenome sequencing reads using a bioinformatics pipeline tailored to the high complexity and diversity of the soil microbiome.

A tree-planting decision support tool for urban heat mitigation.

Heat poses an urgent threat to public health in cities, as the urban heat island (UHI) effect can amplify exposures, contributing to high heat-related mortality and morbidity. Urban trees have the potential to mitigate heat by providing substantial cooling, as well as co-benefits such as reductions in energy consumption. The City of Boston has attempted to expand its urban canopy, yet maintenance costs and high tree mortality have hindered successful canopy expansion.