AI Article Synopsis

  • Arctic snowpack microbial communities are influenced by various atmospheric factors, making their structural complexities essential for evaluating ecological theories like niche-based and neutral assembly.
  • In a study conducted across 22 glacier sites in Svalbard, researchers sampled snow to analyze taxonomic diversity, immigration rates, and chemical composition, utilizing Bayesian methods and multivariate analyses.
  • Findings indicate a combination of neutral and niche-based selection influences microbial communities, with organic acids serving as key predictors of diversity, and the relationship between microbial abundance closely linked to sea spray.

Article Abstract

Background: Arctic snowpack microbial communities are continually subject to dynamic chemical and microbial input from the atmosphere. As such, the factors that contribute to structuring their microbial communities are complex and have yet to be completely resolved. These snowpack communities can be used to evaluate whether they fit niche-based or neutral assembly theories.

Methods: We sampled snow from 22 glacier sites on 7 glaciers across Svalbard in April during the maximum snow accumulation period and prior to the melt period to evaluate the factors that drive snowpack metataxonomy. These snowpacks were seasonal, accumulating in early winter on bare ice and firn and completely melting out in autumn. Using a Bayesian fitting strategy to evaluate Hubbell's Unified Neutral Theory of Biodiversity at multiple sites, we tested for neutrality and defined immigration rates at different taxonomic levels. Bacterial abundance and diversity were measured and the amount of potential ice-nucleating bacteria was calculated. The chemical composition (anions, cations, organic acids) and particulate impurity load (elemental and organic carbon) of the winter and spring snowpack were also characterized. We used these data in addition to geographical information to assess possible niche-based effects on snow microbial communities using multivariate and variable partitioning analysis.

Results: While certain taxonomic signals were found to fit the neutral assembly model, clear evidence of niche-based selection was observed at most sites. Inorganic chemistry was not linked directly to diversity, but helped to identify predominant colonization sources and predict microbial abundance, which was tightly linked to sea spray. Organic acids were the most significant predictors of microbial diversity. At low organic acid concentrations, the snow microbial structure represented the seeding community closely, and evolved away from it at higher organic acid concentrations, with concomitant increases in bacterial numbers.

Conclusions: These results indicate that environmental selection plays a significant role in structuring snow microbial communities and that future studies should focus on activity and growth. Video Abstract.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9979512PMC
http://dx.doi.org/10.1186/s40168-023-01473-6DOI Listing

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