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Record W2021435227 · doi:10.1111/fwb.12247

Differences in feeding behaviour among<i><scp>C</scp>hironomus</i>species revealed by measurements of sulphur stable isotopes and cadmium in larvae

2013· article· en· W2021435227 on OpenAlexaff
Isabelle Proulx, Landis Hare

Bibliographic record

VenueFreshwater Biology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsWater columnBiologyAnoxic watersSympatric speciationStable isotope ratioEcologyChemoclineLarvaCadmiumIsotopes of nitrogenEnvironmental chemistryChemistry

Abstract

fetched live from OpenAlex

Summary We set out to determine the feeding behaviours of 15 C hironomus species collected from 16 boreal forest lakes by measuring cadmium (Cd) and stable isotopes of carbon (C), nitrogen (N) and sulphur (S) in larvae. Measurements of S stable isotopes and Cd discriminated between C hironomus species that feed mainly on oxic particles from those that feed mainly on anoxic particles. Our results suggest that C . dilutus , C . entis , C . plumosus and C . staegeri feed mainly on oxic particles (in the water column, in sediment or both), whereas C . anthracinus , C . bifurcatus , C . cucini , C . decorus ‐group sp. 2, C . harpi , C . nr. atroviridis (sp. 2i), C . ochreatus , C . spp. NAI ‐ NAIII and C . ‘tigris’ feed mainly on anoxic sediments. In our study lakes, larval C isotopic signatures were relatively high, which suggests that they feed little on methanotrophic bacteria. Although larval C and N signatures differed between some sympatric C hironomus species, these differences were not consistent among lakes. The absence of a trend among lakes suggests that lake‐specific factors determine larval C and N signatures. Differences in feeding habits and Cd concentrations among sympatric (cohabiting) C hironomus species suggest that pooling them in ecological, palaeolimnological or ecotoxicological studies could obscure trends in nature, thereby limiting their use as monitors of climate change or pollution.

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 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 score0.075
Threshold uncertainty score0.999

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 studies0.0000.001
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 head0.018
GPT teacher head0.212
Teacher spread0.195 · 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

Citations32
Published2013
Admission routes1
Has abstractyes

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