The influence of habitat selection on Canada Goose Branta canadensis nest success on Akimiski Island, Nunavut, Canada
Bibliographic record
Abstract
Predation avoidance is likely the foremost factor driving nest site selection among ground-nesting birds. The consequences of nest site selection were investigated on nest success for Canada Geese Branta canadensis breeding on Akimiski Island, Nunavut, Canada in 2010. Habitat features were measured at the scale of a nesting territory, at the nest site ( n = 241), and at random locations for both scales. Compared with paired random locations, nests were more likely to be in woody vegetation located closer to water at the territory scale and had less lateral vegetative cover but taller vegetation nearer to the nest site. Geese did not select nesting locations in vegetation that provided maximum cover, but rather located nests in areas providing both concealment from predators and visibility for the nesting female to enable early predator detection. Assessing the effect of habitat attributes on nest success did not yield unambiguous results, with the most parsimonious model showing an increasing probability of nest success with increasing nest age alone. Although nest site selection was not random, we suggest that increasing parental investment and declining predation risk (not likely mutually exclusive) through the breeding season had more influence on Canada Goose nest success on Akimiski Island than did choice of specific habitat features or spacing of nests.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".