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Stable isotope variability of meso‐zooplankton along a gradient of dissolved organic carbon

2009· article· en· W2037934538 on OpenAlexafffund
Anurani D. Persaud, Peter J. Dillon, D. C. Lasenby, Norman D. Yan

Bibliographic record

VenueFreshwater Biology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsOntario Science CentreTrent UniversityYork University
FundersNatural Sciences and Engineering Research Council of CanadaTrent UniversityYork University
KeywordsZooplanktonDissolved organic carbonSestonFood webBranchiopodaCalanoidaDaphniaEcologyIsotopic signatureBiologyStable isotope ratioCladoceraEnvironmental sciencePhytoplanktonCrustaceanPredationNutrientCopepod

Abstract

fetched live from OpenAlex

Summary 1. The δ 13 C and δ 15 N signatures of zooplankton vary with dissolved organic carbon (DOC), but inconsistent and limited taxonomic resolution of previous studies have masked differences that may exist among orders, genera or species and are attributable to dietary and/or habitat differences. Here we investigate differences among the isotopic signatures of five zooplankton taxa ( Daphnia , Holopedium , large Calanoida, small Calanoida and Cyclopoida) in Precambrian shield lakes with a sixfold range of DOC concentration. 2. δ 13 C signatures of Daphnia , small calanoids and large calanoids became more depleted with increasing lake DOC, whereas Holopedium and cyclopoid δ 13 C became enriched with increasing DOC concentration. 3. The variability of δ 13 C and δ 15 N isotopic signatures among zooplankton groups was reduced in high‐DOC, compared to low‐DOC lakes, especially for δ 13 C. Differences in δ 13 C and POM‐corrected δ 15 N accounted for up to 33.7% and 19.5% of the variance, respectively, among lakes of varying DOC concentration. 4. The narrow range of signatures found in higher DOC lakes suggests that different taxa have similar food sources and/or habitats. In contrast, the wide range of signatures in low‐DOC lakes suggests that different taxa are exploiting different food sources and/or habitats. Together with the variable trends in zooplankton isotopic signatures along our DOC gradient, these results suggest that food web dynamics within the zooplankton community of temperate lakes will change as climate and lake DOC concentrations change.

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 score0.015
Threshold uncertainty score0.997

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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

Citations21
Published2009
Admission routes2
Has abstractyes

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