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Record W4401010669 · doi:10.1186/s40793-024-00587-0

Soils of two Antarctic Dry Valleys exhibit unique microbial community structures in response to similar environmental disturbances

2024· article· en· W4401010669 on OpenAlexaff
Mafalda S. Baptista, Charles K. Lee, Maria R. Monteiro, Luı́s Torgo, S. Craig Cary, Catarina Magalhães

Bibliographic record

VenueEnvironmental Microbiome · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMicrobial population biologyBiotaEcologyBiological dispersalSoil waterMicrobial ecologyBiologyMicrobial matBiosphereEnvironmental changeEnvironmental scienceClimate changeBacteria

Abstract

fetched live from OpenAlex

BACKGROUND: Isolating the effects of deterministic variables (e.g., physicochemical conditions) on soil microbial communities from those of neutral processes (e.g., dispersal) remains a major challenge in microbial ecology. In this study, we disturbed soil microbial communities of two McMurdo Dry Valleys of Antarctica exhibiting distinct microbial biogeographic patterns, both devoid of aboveground biota and different in macro- and micro-physicochemical conditions. We modified the availability of water, nitrogen, carbon, copper ions, and sodium chloride salts in a laboratory-based experiment and monitored the microbial communities for up to two months. Our aim was to mimic a likely scenario in the near future, in which similar selective pressures will be applied to both valleys. We hypothesized that, given their unique microbial communities, the two valleys would select for different microbial populations when subjected to the same disturbances. RESULTS: The two soil microbial communities, subjected to the same disturbances, did not respond similarly as reflected in both 16S rRNA genes and transcripts. Turnover of the two microbial communities showed a contrasting response to the same environmental disturbances and revealed different potentials for adaptation to change. These results suggest that the heterogeneity between these microbial communities, reflected in their strong biogeographic patterns, was maintained even when subjected to the same selective pressure and that the 'rare biosphere', at least in these samples, were deeply divergent and did not act as a reservoir for microbiota that enabled convergent responses to change in environmental conditions. CONCLUSIONS: Our findings strongly support the occurrence of endemic microbial communities that show a structural resilience to environmental disturbances, spanning a wide range of physicochemical conditions. In the highly arid and nutrient-limited environment of the Dry Valleys, these results provide direct evidence of microbial biogeographic patterns that can shape the communities' response in the face of future environmental changes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.248
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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