Isotopic Signatures and Trace Elements Concentrations in Breast Feathers of Male Caspian Terns and Double Crested Cormorants
Bibliographic record
Abstract
Migratory fish-eating birds occupy the highest trophic positions of aquatic ecosystems and as such serve as invaluable end-point indicators of the presence and bioaccumulation of anthropogenic contaminants. The birds’ main route of contaminant exposure is through food consumption. Migration can complicate this pathway by introducing numerous feeding habitats and thus, potential sources of contamination. Birds possess a number of depuration mechanisms that permit them to reduce their contaminant burden, namely the elimination of metals and mercury (Hg) through their feathers, feces and eggs. Trace element concentrations found in the feathers reflect the contaminants circulating in the body at the time of feather growth, representing local exposure and potential mobilization from internal tissues. Molt schedules and patterns are important considerations when selecting feathers to link feeding ecology with contaminants, as migratory birds’ feathers grow on and represent different sites. Stable nitrogen (δ15N) and carbon (δ13C) and hydrogen isotopes (δD) can reveal feeding ecology and habitat use during their annual cycle. Consequently, anthropogenic and natural sources of metal accumulation can be linked to those ecological variables. This study will examine the assimilation of trace element in male Caspian Tern (Sterna caspia) and Double-crested Cormorant (Phalacrocorax auritus) breast feathers grown on wintering sites and stable isotope signatures will be used to determine origin of contaminants. The aims for this study are to determine (i) whether isotopic signatures of feathers grown on wintering sites can explain variations in feather trace element concentrations, (ii) whether isotopes can determine the source of contamination, and (iii) whether differences in trace elements between individuals are determined by location of wintering ground or species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".