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Record W1985762228 · doi:10.1642/auk-14-227.1

Improved arrival-date estimates of Arctic-breeding Dunlin (<i>Calidris alpina arcticola</i>)

2015· article· en· W1985762228 on OpenAlexafffund
Andrew Doll, Richard B. Lanctot, Craig A. Stricker, Stephen M. Yezerinac, Michael B. Wunder

Bibliographic record

VenueThe Auk · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsMount Allison University
FundersU.S. Fish and Wildlife ServiceMount Allison UniversityUniversity of Colorado DenverMassachusetts Department of Fish and GameU.S. Geological SurveyAlaska Department of Fish and Game
KeywordsCalidrisArcticEcologyHabitatSandpiperGeographyEnvironmental scienceBiologyPhysical geographyFishery

Abstract

fetched live from OpenAlex

The use of stable isotopes in animal ecology depends on accurate descriptions of isotope dynamics within individuals. The prevailing assumption that laboratory-derived isotopic parameters apply to free-living animals is largely untested. We used stable carbon isotopes (δ13C) in whole blood from migratory Dunlin (Calidris alpina arcticola) to estimate an in situ turnover rate and individual diet-switch dates. Our in situ results indicated that turnover rates were higher in free-living birds, in comparison to the results of an experimental study on captive Dunlin and estimates derived from a theoretical allometric model. Diet-switch dates from all 3 methods were then used to estimate arrival dates to the Arctic; arrival dates calculated with the in situ turnover rate were later than those with the other turnover-rate estimates, substantially so in some cases. These later arrival dates matched dates when local snow conditions would have allowed Dunlin to settle, and agreed with anticipated arrival dates of Dunlin tracked with light-level geolocators. Our study presents a novel method for accurately estimating arrival dates for individuals of migratory species in which return dates are difficult to document. This may be particularly appropriate for species in which extrinsic tracking devices cannot easily be employed because of cost, body size, or behavioral constraints, and in habitats that do not allow individuals to be detected easily upon first arrival. Thus, this isotopic method offers an exciting alternative approach to better understand how species may be altering their arrival dates in response to changing climatic conditions.

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)0.001
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 score0.361
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.253
Teacher spread0.231 · 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

Citations4
Published2015
Admission routes2
Has abstractyes

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