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Abstract: Background: The rRNA operon (rrn) copy number is associated with protein synthesis and reproduction, reflecting microbial r- and K-life strategies and influencing soil ecosystem function. Although the positive relationship between microbial community-level rrn copy numbers and nutrient availability has been reported, the association between rrn copy number and soil stoichiometry or environmental stress remains largely unknown, particularly in the context of long-term nutrient inputs.Results: Using long-term (> 30 years) field experiments across three agro-ecosystems, we consistently found that N fertilization increased the microbial community-level rrn copy number. This increase was equivalently explained by soil CN stoichiometry (22%) and soil acidification (21%). Balanced soil CN stoichiometry favored the growth of N-dependent copiotrophs such as Bacilliand Flavobacteriia containing high rrn copy numbers (an average of 2.5), and enhanced their nutrient competition ability. Moreover, N fertilization-induced soil acidification, as an environmental stressor, increased the abundance of pH-negative responders such as Clostridia and Ktedonobacteria which also contained high rrn copy numbers (2.8), and threatened rare taxa with low rrn copy numbers.Conclusions: Consequently, our finding challenges the concept of microbial life-strategy regulation solely by nutrient availability, highlighting the novelty of significant contributions of soil stoichiometric balance and environmental stress to microbial strategies in agro-ecosystems under long-term nutrient inputs.

Most restoration projects involving invasive plant eradication tend to focus on plant removal with little consideration given to how these invasives change soil microbial communities. However, soil microorganisms can determine invasibility of habitats and, in turn, be altered by invasives once established, potentially inhibiting native plant establishment. We studied soil microbial communities in coastal dunes with varying invasion intensity and different restoration approaches (herbicide, mechanical excavation) at Point Reyes National Seashore. Overall, we found evidence of a strong link between bacterial and fungal soil communities and the presence of invasives and restoration approach. Heavily invaded sites were characterized by a lower abundance of putatively identified nitrifiers, fermentative bacteria, fungal parasites, and fungal dung saprotrophs and a higher abundance of cellulolytic bacteria and a class of arbuscular mycorrhizal fungi (Archaeosporomycetes). Changes in soil microbiota did not fully dissipate following removal of invasives using herbicide, with exception of reductions in cellulolytic bacteria and Archaeosporomycetes abundance. Mechanical restoration effectively removed both invasives and soil legacy effects by inverting or “flipping” rhizome-contaminated surface soils with soils from below and may have inadvertently induced other adverse effects on soils that impeded reestablishment of native dune plants. Land managers should consider additional measures to counteract lingering legacy effects and/or focus restoration efforts in areas where legacy effects are less pronounced.

Co-occurrence networks allow for the identification of potential associations among species, which may be important for understanding community assembly and ecosystem functions. We employed this strategy to examine prokaryotic co-occurrence patterns in the Amazon soils and the response of these patterns to land use change to pasture, with the hypothesis that altered microbial composition due to deforestation will mirror the co-occurrence patterns across prokaryotic taxa. In this study, we calculated Spearman correlations between operational taxonomic units (OTUs) as determined by 16S rRNA gene sequencing, and only robust correlations were considered for network construction (-0.80 ≥ P ≥ 0.80, adjusted P < 0.01). The constructed network represents distinct forest and pasture components, with altered compositional and topological features. A comparative analysis between two representative modules of these contrasting ecosystems revealed novel information regarding changes to metabolic pathways related to nitrogen cycling. Our results showed that soil physicochemical properties such as temperature, C/N and H++Al3+ had a significant impact on prokaryotic communities, with alterations to network topologies. Taken together, changes in co-occurrence patterns and physicochemical properties may contribute to ecosystem processes including nitrification and denitrification, two important biogeochemical processes occurring in tropical forest systems.

It has been known for centuries that microorganisms are ubiquitous in the atmosphere, where they are capable of long-distance dispersal. Likewise, it is well-established that these airborne bacteria and fungi can have myriad effects on human health, as well as the health of plants and livestock. However, we have a limited understanding of how these airborne communities vary across different geographic regions or the factors that structure the geographic patterns of near-surface microbes across large spatial scales. We collected dust samples from the external surfaces of ∼1,200 households located across the United States to understand the continental-scale distributions of bacteria and fungi in the near-surface atmosphere. The microbial communities were highly variable in composition across the United States, but the geographic patterns could be explained by climatic and soil variables, with coastal regions of the United States sharing similar airborne microbial communities. Although people living in more urbanized areas were not found to be exposed to distinct outdoor air microbial communities compared with those living in more rural areas, our results do suggest that urbanization leads to homogenization of the airborne microbiota, with more urban communities exhibiting less continental-scale geographic variability than more rural areas. These results provide our first insight into the continental-scale distributions of airborne microbes, which is information that could be used to identify likely associations between microbial exposures in outdoor air and incidences of disease in crops, livestock, and humans.