Long-term migratory alterations to whooping crane arrival and departure on the wintering and staging grounds
Bibliographic record
Abstract
Climate change can result in alterations to avian behavior, particularly in migratory species. We assessed long-term changes in the endangered whooping crane Grus americana migration phenology in response to temperature, precipitation, and other determinants of migratory behavior. We modeled timing of abundance peaks on the Texas wintering grounds as a function of date and year. During spring and fall migration in central Saskatchewan, we modeled timing of earliest and latest observations, and period of occurrence between them, as a function of year, weather, and wheat production. During winters 1950-2010, the peak abundance period (≥90% of population) shortened. In winter 1950-1951, the peak was 28 November-12 March, but by winter 2010-2011, it was 18 December-20 February. We predict it will shrink to 2 January-6 February by winter 2035-2036. During fall migration 1972-2021, the period cranes occurred in central Saskatchewan lengthened by 20.3 d. In 1971, cranes arrived by 16 September and departed by 17 October, but by 2021 they arrived 12 d earlier (4 September) and departed 17 d later (3 November). We predict a lengthened period of occurrence of 63.8 d by fall 2035 (arrival by 1 September, departure by 8 November). During spring migration 1979-2021, there were no trends in migration phenology (mean period of occurrence was 32 d). Alterations in migration phenology may require modified conservation approaches and consideration of new conservation opportunities. For example, these changes may reduce time cranes spend on the wintering grounds, requiring greater investment in stopover areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".