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Record W1965963076 · doi:10.3354/meps07344

Trophic ecology of siphonostomatoid copepods at deep-sea hydrothermal vents in the northeast Pacific

2007· article· en· W1965963076 on OpenAlexafffundabout
Helene Limén, CJ Stevens, Z Bourass, S. Kim Juniper

Bibliographic record

VenueMarine Ecology Progress Series · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsConcordia UniversityUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsCopepodTrophic levelHydrothermal ventEcologyOceanographyBiologyGeographyCrustaceanHydrothermal circulationGeology

Abstract

fetched live from OpenAlex

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 359:161-170 (2008) - DOI: https://doi.org/10.3354/meps07344 Trophic ecology of siphonostomatoid copepods at deep-sea hydrothermal vents in the northeast Pacific H. Limén1,3,*, C. J. Stevens1,4, Z. Bourass2, S. K. Juniper1,5 1Centre GÉOTOP-UQÀM-McGill, Université du Québec à Montréal, CP 8888 Succursale Centre-Ville, Montréal, Québec H3C 3P8, Canada 2Chemistry and Biochemistry Department, Concordia University, 7141 Sherbrooke St. W., Montréal, Québec H4B 1R6, Canada 3Present address: Research Service, The Swedish Parliament, 100 12 Stockholm, Sweden 4Present address: National Institute of Water and Atmospheric Research, Private Bag 14-901, Kilbirnie, Wellington, New Zealand 5Present address: School of Earth and Ocean Sciences and Department of Biology, University of Victoria, PO Box 3020, Victoria, British Columbia V8W 3N5, Canada *Email: helene.limen@riksdagen.se ABSTRACT: Siphonostomatoid copepods are often numerically important at deep-sea hydrothermal vents but their role in vent food webs has been little investigated. We examined food sources of 2 vent copepod species, Stygiopontius quadrispinosus and Benthoxinus spiculifer, and their potential role in the diet of paralvinellid worms, using a combination of complementary techniques: (1) stable carbon and nitrogen isotopes, (2) fatty acid composition and (3) morphological examination of copepod mouth structures using scanning electron microscopy. All 3 techniques revealed distinct differences between the 2 copepod species. Fatty acid composition identified bacteria as the main food source for both copepod species and indicated that S. quadrispinosus may be more specialised than B. spiculifer. Stable carbon and nitrogen isotopes provided further evidence that the 2 species partition food sources but feed at the same trophic level. The fatty acid composition and stable isotopes of both paralvinellid worms showed that they are generalists, with a varied diet. Further, in samples where S. quadrispinosus were highly abundant, both worms had stable carbon and nitrogen isotopic compositions that indicated that they were feeding on copepods. Although neither worm appeared anatomically equipped for seizing live copepod prey, we suggest that dead copepods may be consumed along with other particulate debris by the paralvinellid worms. The contribution of copepod remains to the detrital pool in these mineral substratum habitats remains to be quantified. KEY WORDS: Hydrothermal vents · Copepoda · Polychaeta · Food webs · Stable isotopes · Fatty acids · Morphology · Northeast Pacific Full text in pdf format PreviousNextCite this article as: Limén H, Stevens CJ, Bourass Z, Juniper SK (2008) Trophic ecology of siphonostomatoid copepods at deep-sea hydrothermal vents in the northeast Pacific. Mar Ecol Prog Ser 359:161-170. https://doi.org/10.3354/meps07344 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 359. Online publication date: May 05, 2008 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2008 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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.996

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.004
GPT teacher head0.217
Teacher spread0.213 · 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

Citations28
Published2007
Admission routes3
Has abstractyes

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