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Record W4415559713 · doi:10.1101/2025.10.25.684473

Utility of alternate stable isotope calibration equations and informative priors when estimating the breeding origin of Arctic-breeding shorebirds

2025· preprint· W4415559713 on OpenAlexaffabout
Devin R. de Zwaan, Julie Paquet, Rebeca C. Linhart, Erica Nol, Paul A. Smith, Diana J. Hamilton

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Language
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsMount Allison UniversityTrent UniversityEnvironment and Climate Change Canada
Fundersnot available
KeywordsPrior probabilityCalibrationArcticFeatherStable isotope ratioBayesian probability

Abstract

fetched live from OpenAlex

Abstract Understanding migratory connectivity is essential for monitoring and conserving Arctic-breeding shorebirds, particularly given divergent rates of decline across populations. Stable hydrogen isotope analysis of feathers offers a scalable, non-invasive method to assign breeding origin, but current applications are limited by the absence of shorebird-specific calibration equations, which associate feather isotope values with environmental isotope gradients (“isoscapes”), and by longitudinal isoscape bands in the Arctic that result in diffuse origin estimates across broad, heterogeneous regions. We evaluated the utility of alternate calibration equations and the incorporation of occupancy-based informative priors for improving breeding origin assignments. Specifically, we analyzed feather isotope data from hatch-year semipalmated sandpipers ( Calidris pusilla ) captured at staging sites in the Canadian Maritimes, as well as known-origin Arctic samples, to compare calibration equations from different reference datasets and test priors derived from eBird habitat occupancy predictions. We demonstrate that Arctic samples of known origin largely align with calibration equations based on broad passerine datasets, although incorporating Arctic samples into the calibration may correct for a marginal westward bias in origin estimates. Using occupancy-based priors that reflect habitat preferences increased precision by 18.8%, identifying ‘hotspots’ within otherwise expansive isotopic bands. We highlight the validity of existing reference datasets with broad geographic coverage and demonstrate the value of informative priors to refine origin estimates. We recommend expanding Arctic sample collections across a wider longitudinal gradient to define a shorebird-specific calibration equation and further exploring potential biases in prior data sources to improve accuracy of Arctic-breeding shorebird origin assignments.

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)0.024
metaresearch head score (Gemma)0.072
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.072
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.247
Teacher spread0.223 · 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 designSimulation or modeling
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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicAvian ecology and behavior→French-language works237,207→