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Record W4247936028 · doi:10.1093/auk/121.1.170

Blood Isotopic (δ13C and δ15N) Turnover and Diet-Tissue Fractionation Factors in Captive Dunlin (Calidris Alpina Pacifica)

2004· article· en· W4247936028 on OpenAlexaff
Lesley J. Evans Ogden, Keith A. Hobson, David B. Lank

Bibliographic record

VenueThe Auk · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCalidrisδ13CTurnoverδ15NFractionationBiologyIsotopeIsotopes of nitrogenStable isotope ratioIsotope analysisAnimal scienceZoologyEcologyChemistryPredationChromatography

Abstract

fetched live from OpenAlex

Abstract Avian studies are often interpreted using dual (e.g. 13C, 15N) isotope models, assuming turnover of both isotopes occur at similar rates, but only a few studies have quantified turnover rates for more than one of those isotopes simultaneously. To test the generality of previous turnover and fractionation estimates and assumption of synchronous C and N patterns of turnover rates, we captured Dunlin (Calidris alpina pacifica) wintering in the Fraser River Delta, British Columbia, and derived isotopic turnover rates and diet-tissue fractionation factors by experimentally manipulating diet. Birds (n = 15) were initially fed a terrestrially derived diet (mean δ13C: −24.7‰, mean δ15N: 3.5‰) for 54 days. A treatment group (n = 11) was then switched to a marine-derived diet (mean δ13C: −18.3‰, mean δ15N: 13.7‰); a control group (n = 4) was maintained on the terrestrial diet for a further 59 days. An exponential model described patterns of isotopic turnover for 13C and 15N, and turnover rates and half-lives of the two isotopes were correlated, confirming the assumption of synchronous patterns of turnover for those isotopes. The half-lives for 13C and 15N in Dunlin whole blood were 11.2 ± 0.8 days and 10.0 ± 0.6 days, respectively, and are among the lowest values obtained to date for wild birds. Variation in turnover rate among individuals was not related to indices of body condition.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.530

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.225
Teacher spread0.218 · 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.

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

Citations43
Published2004
Admission routes1
Has abstractyes

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