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Record W2060762679 · doi:10.1139/z03-140

Isotopic fractionation and turnover in captive Garden Warblers (<i>Sylvia borin</i>): implications for delineating dietary and migratory associations in wild passerines

2003· article· en· W2060762679 on OpenAlexfundvenueno aff
Keith A. Hobson, Franz Bairlein

Bibliographic record

VenueCanadian Journal of Zoology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
FundersUniversity of Saskatchewan
KeywordsFeatherBiologyTrophic levelIsotopes of nitrogenStable isotope ratioδ15NZoologyIsotope analysisIsotopeEcologyFractionationδ13CTurnoverAnimal scienceBotanyChemistry

Abstract

fetched live from OpenAlex

There is currently a great deal of interest in using stable-isotope methods to investigate diet and migratory connections in wild passerines. To apply these methods successfully, it is important to understand how stable isotopes discriminate or change between diet and the tissue of interest and what the element-turnover rates are in metabolically active tissues. Of particular use are studies that sample birds non-destructively through the use of blood and feathers. We investigated patterns of isotopic discrimination between diet and blood and feathers of Garden Warblers (Sylvia borin) raised on an isotopically homogeneous diet (48% C, 5% N) and then switched to one of two experimental diets, mealworms (56.8% C, 8.3% N) and elderberries, Sambucus niger (47.4% C, 1.5% N). We established that the discrimination factors between diet and blood appropriate for stable carbon (δ 13 C) and nitrogen (δ 15 N) isotopes are +1.7‰ and +2.4‰, respectively. For feathers, these values were +2.7‰ and +4‰, respectively. Turnover of elemental nitrogen in whole blood was best approximated by an exponential-decay model with a half-life of 11.0 ± 0.8 days (mean ± SD). Corresponding turnover of carbon was estimated to range from 5.0 ± 0.7 to 5.7 ± 0.8 days. We conclude that this decoupling of nitrogen- and carbon-turnover rates can be explained by differences in metabolic routing of dietary macromolecules. Our results suggest that tracking frugivory in migratory passerines that switch diets between insects and fruits may be complicated if only a trophic-level estimate is made using δ 15 N measurements.

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 score0.701
Threshold uncertainty score0.523

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 head0.013
GPT teacher head0.239
Teacher spread0.226 · 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

Citations163
Published2003
Admission routes2
Has abstractyes

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