Life‐history and demographic variation in an alpine specialist at the latitudinal extremes of the range
Bibliographic record
Abstract
Abstract Alpine environments are unique systems to examine variation in life‐history strategies because temperature and seasonality are similar across broad latitudinal gradients. We studied the life‐history strategies, demography and population growth of white‐tailed ptarmigan Lagopus leucura, an alpine specialist, at the latitudinal extremes of the range in the Yukon (YK, studied from 2004 to 2008) and Colorado (CO, 1987–1996). The two populations were separated by 2,400 km of latitude, and the Yukon site was approximately 2,000 m lower in elevation than the Colorado site. Yukon females bred on average 9 days earlier than those in Colorado, but the latter study was conducted 15 years earlier and breeding dates may have advanced over this period. The length of the breeding season was similar between the two populations, and females had comparable probabilities of re‐nesting after failure. The two populations differed in how they allocated effort to the first clutch as Yukon females laid larger clutches (7.1 vs. 5.9 eggs) but smaller eggs (18.8 vs. 20.5 g) than those in Colorado. Demographic rates also differed; nest survival was higher in the Yukon (0.40) than in Colorado (0.24), and the resultant annual fecundity was nearly twice as high in the Yukon (3.92 vs. 1.77 chicks/female). In contrast, annual adult survival was higher in Colorado although the confidence intervals overlapped (females: YK = 0.35, CO = 0.44; males: YK = 0.48, CO = 0.59). Estimates of annual population growth (λ) indicated both populations were declining, especially in Colorado (λYK = 0.83, λCO = 0.66), and thus, dispersal movements are likely key to long‐term persistence in both cases. Our findings suggest that breeding‐season temperature and seasonality affect measures related to timing of reproduction, but not the costs and benefits of clutch and egg size.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".