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Record W2122136925 · doi:10.1038/ismej.2012.138

Effects of patch connectivity and heterogeneity on metacommunity structure of planktonic bacteria and viruses

2012· article· en· W2122136925 on OpenAlexafffund
Steven Declerck, Christian Winter, Jonathan B. Shurin, Curtis A. Suttle, Blake Matthews

Bibliographic record

VenueThe ISME Journal · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of British Columbia
FundersVlaamse regeringNatural Sciences and Engineering Research Council of CanadaFonds Wetenschappelijk OnderzoekSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungTula Foundation
KeywordsMetacommunityBiological dispersalBiologyEcologyPlanktonBiodiversityMicrobial ecologyBacterioplanktonZooplanktonCommunity structureBeta diversitySpatial ecologyPhytoplanktonBacteriaNutrientPopulation

Abstract

fetched live from OpenAlex

Dispersal limitation is generally considered to have little influence on the spatial structure of biodiversity in microbial metacommunities. This notion derives mainly from the analysis of spatial patterns in the field, but experimental tests of dispersal limitation using natural communities are rare for prokaryotes and, to our knowledge, non-existent for viruses. We studied the effects of dispersal intensity (three levels) and patch heterogeneity (two levels) on the structure of replicate experimental metacommunities of bacteria and viruses using outdoor mesocosms with plankton communities from natural ponds and lakes. Low levels of dispersal resulted in a decrease in the compositional differences (beta diversity) among the communities of both bacteria and viruses, but we found no effects of patch heterogeneity. The reductions in beta diversity are unlikely to be a result of mass effects and only partly explained by indirect dispersal-mediated interactions with phytoplankton and zooplankton. Our results suggest that even a very limited exchange among local communities can alter the trajectory of bacterial and viral communities at small temporal and spatial scales.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.250
Teacher spread0.239 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations88
Published2012
Admission routes2
Has abstractyes

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