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Record W2102408601 · doi:10.4319/lo.2008.53.2.0411

Explaining metal concentrations in sympatric <i>Chironomus</i> species

2008· article· en· W2102408601 on OpenAlexafffund
Sylvain Martin, Isabelle Proulx, Landis Hare

Bibliographic record

VenueLimnology and Oceanography · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChironomusCadmiumSedimentLarvaEnvironmental chemistrySympatric speciationMetalZincBiologyEcologyChironomidaeChemistry

Abstract

fetched live from OpenAlex

We compared metal concentrations in larvae of two Chironomus species (Chironomus staegeri and Chironomustigris) living in the same lake and at the same depth and time. Concentrations of the nonessential metal cadmium (Cd) differed greatly (>8x) between the two species, whereas those of two essential metals differed either much less (zinc [Zn], 2x) or not at all (copper [Cu]). These trends were constant in all seasons. On the one hand, differences in Cd and Zn concentrations between the species were not explained by differences in either their size or their life cycle. Likewise, differential exposure to dissolved metals did not explain larval Cd and Zn concentrations because vertical gradients in dissolved metals did not correlate with depths of larval feeding. On the other hand, the species differed in the type of sediment that they consumed, and measurements of sulfur stable isotopes in larvae confirmed that whereas C. staegeri consumes mostly surface oxic sediment, C. tigris eats mainly deeper anoxic sediment. Because total metal concentrations in gut contents were not correlated with those in larvae, it is likely that metal bioavailability differs between the two sediment types. Overall, our results show that because metal concentrations can differ widely between sympatric congeners, extrapolation from one Chironomus species to another may not be justifiable. Furthermore, because larvae exposed to Zn in the laboratory did not accumulate this metal as they would in the field, we suggest that care is warranted when extrapolating from results obtained in laboratory tests to animals living in the field.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.193
Teacher spread0.181 · 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

Citations34
Published2008
Admission routes2
Has abstractyes

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