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Record W1970573481 · doi:10.3354/ame045181

Size independent selective filtration of ultraplankton by hexactinellid glass sponges

2006· article· en· W1970573481 on OpenAlexafffund
Gitai Yahel, DI Eerkes-Medrano, Sally P. Leys

Bibliographic record

VenueAquatic Microbial Ecology · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsUniversity of AlbertaUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of AlbertaUniversity of Victoria
KeywordsFjordBiologyEcologyPelagic zoneBenthic zonePredationHabitatOceanography

Abstract

fetched live from OpenAlex

AME Aquatic Microbial Ecology Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials AME 45:181-194 (2006) - doi:10.3354/ame045181 Size independent selective filtration of ultraplankton by hexactinellid glass sponges Gitai Yahel1,*, Dafne I. Eerkes-Medrano1,3, Sally P. Leys2 1Department of Biology, University of Victoria, PO Box 3020 Stn CSC, Victoria, British Columbia V8W 3N5, Canada 2Department of Biological Sciences, CW 405, Department of Biological Sciences, University of Alberta, Edmonton, Alberta T6G 2E9, Canada 3Present address: Department of Zoology, Oregon State University, Corvallis, Oregon 97331-2914, USA *Email: yahel@uvic.ca ABSTRACT: Selective feeding by flagellate and ciliate protists is important in shaping microbial communities in pelagic habitats. While less is known of predation on microbial communities in benthic habitats, the abundance and high filtering capacity of sponges suggests that they are key grazers. We studied the feeding preferences of two of the most common glass sponges of North-East Pacific fjords, Rhabdocalyptus dawsoni and Aphrocallistes vastus. Sponges were maintained in large darkened tanks supplied with running seawater from the nearby fjord. The water inhaled and exhaled by the sponges was simultaneously sampled and analyzed using a flow cytometer. Both sponges showed a similar (but not identical) feeding pattern, efficiently removing up to 99% of the most abundant bacterial cells, whereas clays, silt, and 'debris' particles were expelled into the exhaled water. Filtration efficiencies were maximal for the relatively large and rare eukaryotic algae (3 to 5 µm, 86 ± 9%) and for small non-photosynthetic bacteria (<0.4 µm, 89 ± 10%), while intermediate sized non-photosynthetic bacteria characterized by higher nucleic acid content were efficiently removed in February (92 ± 3%) when overall plankton concentration was low, but not in July (28 ± 16%). The intermediate sized photosynthetic prokaryote Synechococcus (1.1 to 1.5 µm) was also less preferred. Detailed analysis of the ultrastructure of the glass sponge filtration apparatus argues against possible 'by-pass' routes. We suggest that selective filtration involves individual processing, recognition, sorting, and transport of each particle through the sponges' syncytial tissue. Selective grazing by glass sponges, like their pelagic protozoan counterparts, could be an important mechanism shaping microbial communities in the detrital food web of North-East Pacific fjords. KEY WORDS: Selective feeding · Filtration · Aphrocallistes vastus · Rhabdocalyptus dawsoni Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in AME Vol. 45, No. 2. Online publication date: November 24, 2006 Print ISSN: 0948-3055; Online ISSN: 1616-1564 Copyright © 2006 Inter-Research.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.003
GPT teacher head0.203
Teacher spread0.200 · 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

Citations85
Published2006
Admission routes2
Has abstractyes

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