IMPACTS OF GLOBAL AND REGIONAL CLIMATE ON WHOOPING CRANE\nDEMOGRAPHY: TRENDS AND EXTREME EVENTS
Bibliographic record
Abstract
We analyzed long-term demographic and environmental data to understand the role of large scale climatic factors (the Pacific Decadal Oscillations [PDO]) and environmental factors in 3 regions of North America on natality and mortality of the remnant migratory whooping crane (Grus americana) population. This is an endangered species that spends winters at Aransas National Wildlife Refuge (ANWR) in Texas, breeds at Wood Buffalo National Park (WBNP) in Canada and “…uses Nebraska as a primary stopover”. Long term data (27 years) of demography and environmental factors (PDO index, temperature and precipitation at WBNP, Nebraska and ANWR, pond water depth at WBNP, freshwater inflow, and net evaporation at wintering ground) were analyzed. Multiple regression analysis (path analysis) and qualitative analysis determined mechanisms (trends and extreme events) affecting whooping crane dynamics. Changes in mortality of eggs, chicks, juveniles during fall migration and at wintering grounds, and adults and subadults at wintering grounds, from April to November and annually, were correlated with environmental factors from the 3 different regions (except net evaporation at ANWR and temperature and precipitation in Nebraska during spring migration). Natality variability (brood failure and clutch size reduction) was explained by PDO, pond water depth in WBNP and environmental factors from the wintering ground that affected pre-breeding conditions and subsequently reproduction. Qualitative analysis showed synchrony of extreme events at ANWR and WBNP and extreme effects on whooping crane demography. Direct and indirect effects of these environmental factors are discussed at the population and individual level.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".