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Record W2065537854 · doi:10.1038/ismej.2014.89

Can marine bacteria be recruited from freshwater sources and the air?

2014· article· en· W2065537854 on OpenAlexaff
Jérôme Comte, Eva S. Lindström, Alexander Eiler, Silke Langenheder

Bibliographic record

VenueThe ISME Journal · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversité Laval
FundersSvenska Forskningsrådet FormasVetenskapsrådetStiftelsen för Strategisk ForskningUppsala Multidisciplinary Center for Advanced Computational ScienceWenner-Gren Stiftelserna
KeywordsBiological dispersalBiologyEcologyGeneralist and specialist speciesPelagic zoneTaxonHabitatSedimentNicheMarine habitatsPopulation

Abstract

fetched live from OpenAlex

There is now clear evidence that microorganisms present biogeographic patterns, yet the processes that create and maintain them are still not well understood. In particular, the contribution of dispersal and its exact impact on local community composition is still unclear. For example, dispersing cells may not thrive in recipient environments, but may still remain part of the local species pool. Here, we experimentally tested if marine bacteria can be retrieved from freshwater communities (pelagic and sediment) and the atmosphere by exposing bacteria from three lakes, that differ in their proximity to the Norwegian Sea, to marine conditions. We found that the percentage of freshwater taxa decreased with increasing salinities, whereas marine taxa increased along the same gradient. Our results further showed that this increase was stronger for lake and sediment compared with air communities. Further, significant increases in the average niche breadth of taxa were found for all sources, and in particular lake water and sediment communities, at higher salinities. Our results therefore suggests that marine taxa can readily grow from freshwater sources, but that the response was likely driven by the growth of habitat generalists that are typically found in marine systems. Finally, there was a greater proportion of marine taxa found in communities originating from the lake closest to the Norwegian Sea. In summary, this study shows that the interplay between bacterial dispersal limitation and dispersal from internal and external sources may have an important role for community recovery in response to environmental change.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.000

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 head0.010
GPT teacher head0.198
Teacher spread0.187 · 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 teacher head, not a consensus.

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

Citations68
Published2014
Admission routes1
Has abstractyes

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