Our planet teems with microorganisms that often present a skewed abundance distribution in a local community, with relatively few dominant species coexisting alongside a high number of rare species. Recent studies have demonstrated that these rare taxa serve as limitless reservoirs of genetic diversity, and perform disproportionate types of functions despite their low abundances. However, relatively little is known about the mechanisms controlling rarity and the processes promoting the development of the rare biosphere. Here, we propose the use of multivariate cut-offs to estimate rare species and phylogenetic null models applied to predefined rare taxa to disentangle the relative influences of ecoevolutionary processes mediating the assembly of the rare biosphere. Importantly, the identification of the factors controlling rare species assemblages is critical for understanding the types of rarity, how the rare biosphere is established, and how rare microorganisms fluctuate over spatiotemporal scales, thus enabling prospective predictions of ecosystem responses.

Summary Soil microbial communities are often not resistant to the impact caused by microbial invasions, both in terms of structure and functionality, but it remains unclear whether these changes persist over time. Here, we used three strains of Escherichia coli O157:H7 (E. coli O157:H7), a species used for modelling bacterial invasions, to evaluate the resilience of the bacterial communities from four Chinese soils to invasion. The impact of E. coli O157:H7 strains on soil native communities was tracked for 120 days by analysing bacterial community composition as well as their metabolic potential. We showed that soil native communities were not resistant to invasion, as demonstrated by a decline in bacterial diversity and shifts in bacterial composition in all treatments. The resilience of native bacterial communities (diversity and composition) was inversely correlated with invader's persistence in soils (R2 = 0.487, p < 0.001). Microbial invasions also impacted the functionality of the soil communities (niche breadth and community niche), the degree of resilience being dependent on soil or native community diversity. Collectively, our results indicate that bacteria invasions can potentially leave a footprint in the structure and functionality of soil communities, indicating the need of assessing the legacy of introducing exotic species in soil environments.

Quantifying which assembly processes structure microbiomes can assist prediction, manipulation, and engineering of community outcomes. However, the relative importance of these processes might depend on whether DNA or RNA are used, as they differ in stability. We hypothesized that RNA-inferred community responses to (a)biotic fluctuations are faster than those inferred by DNA; the relative influence of variable selection is stronger in RNA-inferred communities (environmental factors are spatiotemporally heterogeneous), whereas homogeneous selection largely influences DNA-inferred communities (environmental filters are constant). To test these hypotheses, we characterized soil bacterial communities by sequencing both 16S rRNA amplicons from the extracted DNA and RNA transcripts across distinct stages of soil primary succession and quantified the relative influence of each assembly process using ecological null model analysis. Our results revealed that variations in α-diversity and temporal turnover were higher in RNA- than in DNA-inferred communities across successional stages, albeit there was a similar community composition; in line with our hypotheses, the assembly of RNA-inferred community was more closely associated with environmental variability (variable selection) than using the standard DNA-based approach, which was largely influenced by homogeneous selection. This study illustrates the need for benchmarking approaches to properly elucidate how community assembly processes structure microbial communities.

Atmospheric nitrogen (N) deposition, generally, has been simulated through a single or relatively few N applications per year for its ecological effect study. Despite the importance of timing in ecosystem processes, ecological experiments with more realistic N addition frequencies are rare. We employed a novel design with typical twice (2X) versus atypical monthly (12X) N applications per year to explore effects of N addition frequency on above‐ and below‐ground biodiversity and function. Each year, several response variables from either below‐ground or above‐ground growth, N status and cycling, or plant and bacterial diversity differed as a result of N addition frequency. BNPP showed a large frequency effect in the relatively moist year but not in the dry year. Nitrogen addition decreased root growth in the monthly relative to the biannual applications, which could be highly consequential for predicting changes in global carbon and nitrogen cycling. Simulated N deposition tended to perturb biodiversity, but it is noteworthy that 12X applications that spread N deposition more evenly through a year have much less negative impacts on plant and bacterial diversities than 2X amendments per year. Soil N mineralization rate in year 6 was much lower when N additions were monthly compared with a biannual amendment, especially when simulated N deposition was high. We have established that amendment frequency matters for understanding ecosystem response to N deposition. Experiments that more closely mimic the anthropogenic process of N deposition are needed to best assess ecosystem and potential global biogeochemical changes. A free Plain Language Summary can be found within the Supporting Information of this article.

Most ecological communities harbor many rare species (i.e., the rare biosphere), however, relatively little is known about how distinct ecological processes structure their existence. Here, we used spatiotemporal data on soil bacterial communities along a natural ecosystem gradient to model the relative influences of assembly processes structuring the rare and common biospheres. We found a greater influence of homogeneous selection (i.e., imposed by spatiotemporally constant variables) mediating the assembly of the rare biosphere, whereas the common biosphere was mostly governed by variable selection (i.e., imposed by spatial and/or temporal fluctuating variables). By partitioning the different types of rarity, we found homogeneous selection to explain the prevalence of permanently rare taxa, thus suggesting their persistence at low abundances to be restrained by physiological traits. Conversely, the dynamics of conditionally rare taxa were mostly structured by variable selection, which aligns with the ability of these taxa to switch between rarity and commonness as responses to environmental spatiotemporal variations. Taken together, our study contributes to the establishment of a link between conceptual and empirical developments in the ecology of the soil microbial rare biosphere. Besides, this study provides a framework to better understand, model, and predict the existence and dynamics of microbial rare biospheres across divergent systems and scales.

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Hybrid knowledge representation schemes, including production rules, object-oriented programming, and procedural methods, are employed to express expert heuristics and standard emergency knowledge during the development of the knowledge-based system (KBS) for emergency decision for disaster reduction. This approach renders it possible to take advantages of the characteristics of each method. The system can provide the user with advice on Preliminary plan evaluation, Plan optimization, Plan evaluation ,Plan summary and Miscellaneous.