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Record W7094380365

Temporal Migration Shifts in the Aransas-Wood Buffalo Population of Whooping Cranes (<i>Grus americana</i>) Across North America

2017· article· W7094380365 on OpenAlexaboutno aff

Bibliographic record

VenueInsecta mundi · 2017
Typearticle
Language
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsGrus (genus)ForagingEndangered speciesPopulationPhenologyBird migration
DOInot available

Abstract

fetched live from OpenAlex

Birds are altering the phenology of critical life history events, including migration, in response to the effects of global climate change. Whooping Cranes (Grus americana) are one of the most critically endangered birds in the world. Their remnant population, referred to as the Aransas-Wood Buffalo Population, numbers between 300-400 individuals and migrates between the U.S. Gulf of Mexico coast and north-central Canada twice each year. Previous analyses suggested Whooping Crane migration was temporally constant in spring and fall. New analyses of observations spanning 1942-2016 show Whooping Crane migration is now occurring earlier in spring by approximately 22 days and later in fall by approximately 21 days. Spring temperatures have also increased in the migration corridor during the same period; however, there is no apparent temperature pattern during the fall. In spring, earlier migrating Whooping Cranes stopped over for longer periods of time compared to late-migrating cranes. This result may be partially explained by single Whooping Cranes migrating with earlier migrating Sandhill Cranes (Antigone canadensis). These results have important conservation implications as the timing of Whooping Crane migration and availability of the habitat and foraging resources, including those associated with agriculture, on which this species relies will be increasingly affected by climate change.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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