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Can a ‘wintering area effect’ explain population status of Swainson's hawks? A stable isotope approach

2008· article· en· W2160893073 on OpenAlexaff
José Hernán Sarasola, Juan J. Negro, Keith A. Hobson, Gary R. Bortolotti, Keith L. Bildstein

Bibliographic record

VenueDiversity and Distributions · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of SaskatchewanEnvironment and Climate Change Canada
Fundersnot available
KeywordsButeoFlockRange (aeronautics)EcologyGeographyPopulationAccipiterWildlifeFisheryBiologyPredationDemography

Abstract

fetched live from OpenAlex

ABSTRACT It has been suggested that declines in breeding populations of Swainson's hawks ( Buteo swainsoni ) in California, Oregon, and Nevada may be due to differential mortality of hawks on their wintering grounds. Although massive mortality incidents reported on the wintering grounds partially support this suggestion, there are no data showing differential use of wintering areas by breeding populations of Swainson's hawks. We used stable‐hydrogen isotope analysis of feathers to determine whether large flocks of hawks wintering in Argentina consisted of a mixture of individuals from across the North American breeding range or consisted of individuals from discrete breeding populations. We found that flocks of wintering Swainson's hawks consisted of a mixture of individuals. The lack of connectivity between populations of breeding and wintering hawks suggests that high wintering mortality, either natural or human‐induced, is unlikely to have direct consequences on a single breeding area in North America. The demographic effects of winter mortality should be ‘diluted’ across the entire breeding range of Swainson's hawks.

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 score0.003
Threshold uncertainty score0.794

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 studies0.0010.000
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 head0.021
GPT teacher head0.207
Teacher spread0.186 · 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

Citations22
Published2008
Admission routes1
Has abstractyes

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