Post-moult distribution and abundance of white-fronted geese and Canada geese in West Greenland in 2007
Bibliographic record
Abstract
Rapid increases in North American Canada geese (Branta canadensis) summering in West Greenland since the mid-1980s compare with declines in the endemic population of white-fronted geese (Anser albifrons flavirostris) nesting in the same region since 1999 (wintering in Europe). To provide information on the distribution and abundance of the two species in Greenland during the prelude to the autumn migration back to winter quarters, we here report on the first ever post-moult aerial surveys of West Greenland between 64° and 73°N (from regular transects and transit reconnaissance flights in August 2007), which located 1888 Greenland white-fronted geese and 6071 Canada geese. Strip transect surveys found 733 Greenland white-fronted geese and 1318 Canada geese in the 993 km2 surveyed, which, given a white-fronted goose global population of 23 200 in winter 2007/08, suggests more than 41 500 Canada geese inWest Greenland post-moult in 2007. Virtually no geese were found south of 66°N. The Eqalummiut nunaat–Nassuttuup nunaa and Naternaq Ramsar wetlands of international importance, and lowland Disko Island, Saqqaqdalen and Svartenhuk supported the highest densities of both species. Results confirmed that areas important for both species during spring, nesting and moulting periods retain high densities of post-moulting geese. Canada and white-fronted geese rarely occurred together within 2.5 km ¥ 400 m transect sectors, as found during breeding surveys. Only in western Svartenhuk and western Disko were there Canada goose concentrations that could potentially support an intensive autumn hunt, whilst avoiding disturbance to white-fronted 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".