Påverkar kanadagässen Branta canadensis häckningsresultatet för smålom Gavia stellata och storlom G. arctica?
Bibliographic record
Abstract
During the latest decades, Canada Geese have increased in numbers and expanded over large parts of north-western Europe. Hitherto, the risk for adverse effects on the native bird fauna has been assessed to be negligible, although there are single records of divers (Gavia spp.) having failed or abandoned the breeding site after the establishment of Canada Geese. Therefore, we initiated an inquiry about breeding success and nest locations of divers and geese in Sweden. For Red-throated Diver, we compared the breeding success for pairs nesting at tarns with and without breeding Canada Geese. We found no indication of any negative effects on breeding success: The average production was 0.82 “large” chicks per pair and year for pairs at tarns with breeding Canada Geese, compared to 0.75 at tarns without breeding geese. For Black-throated Diver, the average hatching success for pairs with and without nesting Canada Geese on the same islet was 46% and 47%, respectively. But the average distance to the closest goose nest (on another islet) was lower for failed nests compared to successful ones. We judge, that the expansion of the Canada Goose is not a threat on a national or regional scale, although single diver pairs certainly suffer from having Canada Geese as close neighbours. Among both species of divers there are also indications of adaptations to the geese, e.g. through moving to new nesting sites at the same breeding lake. Finally, potential benefits from the presence of Canada Geese, e.g. if the geese keep other potential predators away, should not be overlooked.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.068 | 0.029 |
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".