Nest Survival and Density of Cackling Geese (Branta Hutchinsii) Inside and Outside a Ross's Goose (<i>Chen Rossii</i>) Colony
Bibliographic record
Abstract
The influence of heterospecifics on successful avian reproduction remains poorly understood, despite the role that such relationships may play in the evolution of reproductive strategies. We estimated nest survival of Cackling Geese (Branta hutchinsii) near McConnell River, Nunavut, in 2004 and 2005 in relation to (1) nest initiation date; (2) nest age; (3) nesting habitat; (4) presence in or absence from a colony composed mainly of Ross's Geese (Chen rossii); and (5) density of neighboring Lesser Snow Geese (C. caerulescens caerulescens) and Ross's Geese. We also assessed whether there was any consistent pattern in nest densities of Cackling Geese inside and outside the colony, using distance sampling methods that account for imperfect detection. Nest survival declined both with later nesting and with increased densities of surrounding Lesser Snow Geese and Ross's Geese, independently of whether or not Cackling Geese nested in the Ross's Goose colony. However, despite these negative interspecific effects at the neighborhood scale, nests had higher survival probabilities inside the colony than outside it when we controlled for nest initiation date and density of neighboring Lesser Snow Goose and Ross's Goose nests. There was no consistent difference in nest densities of Cackling Geese nesting inside and outside the colony. We conclude that Cackling Geese coincidentally establish nest sites inside the colony; the best nest locations are in low-density areas of the colony, but the location of these areas is unpredictable among years because Ross's Geese usually initiate nests later than Cackling Geese.
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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 | 0.001 |
| 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".