Density‐dependent and phenological mismatch effects on growth and survival in lesser snow and Ross's goslings
Bibliographic record
Abstract
Strong seasonality of high‐latitude environments imposes temporal constraints on forage availability and quality for keystone herbivores in terrestrial arctic ecosystems, including hyper‐abundant colonial geese. Changes in food quality due to intraspecific competition, or food availability relative to the breeding phenology of birds, may have consequences for growth and survival of young. We used long‐term data (1993–2014) from the Karrak Lake nesting colony in the Canadian central arctic to study relative roles of density and phenological mismatch (i.e. days between seasonal peaks in vegetation quality and hatching) as drivers of annual variations in gosling survival among lesser snow Anser caerulescens caerulescens and Ross's geese A. rossii . Survival of Ross's goslings was consistently higher compared to snow geese. For both species, annual gosling survival was greatest when phenological mismatch was minimal and when nesting population size was low. We also examined gosling structural size (1999–2014) in relation to density and mismatch hypotheses to understand whether changes in survival were preceded by a parallel response in growth stemming from a density‐dependent effect on annual forage conditions. After controlling for sex, age and random effects of capture group and year × species, structural size of both snow and Ross's goslings was reduced in years when phenological mismatch was greater. However, there was no significant evidence that body size of goslings was negatively related to breeding population size at the colony. Our results lend support to the notion that both broad‐scale changes in seasonality from observed and predicted warming in the arctic and, to a lesser extent, density‐dependence on brood‐rearing areas may result in changes to offspring quality or survival, with implications for population recruitment.
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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) | 0.000 | 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".