Overlap in diet and distribution of two goose species suggests potential for competition at a common moulting area in West Greenland
Bibliographic record
Abstract
Inter-specific competition can occur where two or more species overlap in diet and/or spatial distribution. Such interactions might be most prevalent where a species invades areas previously occupied by another species. In West Greenland, the number of native Greenland White-fronted Geese has decreased over the last 15-20 years, while the Canada Goose, a species new to the area, has increased. This study explores the overlap in diet and space use of these species in Mudderbugten and Kvandalen, together with factors that could influence the degree of competition between the two species. Data on activity budgets and spatial distribution were obtained from observations of behaviour, and diet selection was determined through analyses of plant epidermal fragments in faecal samples that were subsequently genotyped to goose species. No differences in diet or spatial distribution of the two species were found, and behavioural observations indicated only slight modifications in attentive behaviour and increased distance to the lakeshore in sympatry. This would seem to imply that the area has sufficient space and forage to support both species. If so, the local decline in Greenland White-fronted Goose may reflect population fluctuations for reasons other than the increased presence of the Canada Goose.
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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 | 0.001 | 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".