An approach to the assessment of change in the numbers of Canada Geese<i>Branta canadensis</i>and Greylag Geese<i>Anser anser</i>in southern Britain
Bibliographic record
Abstract
Capsule Population change in geese was assessed using an approach that requires a relatively small sampling effort. Aims During the 1999 breeding season a survey was carried out to determine if the numbers of introduced Canada and re-established Greylag Geese in southern Britain had changed since 1988–91 and whether any change had occurred in areas with previously high or low Canada Goose densities. Methods A randomized stratified sample of 246 tetrads from the 24 156 tetrads covered between 1988–91 in this area, as part of the New Atlas of Breeding Birds, were resurveyed. Eight habitat categories were used in the stratification and were based on 1-km-square summary data obtained from the CEH Land Cover Map of Great Britain (water cover and urbanization) and LANDCLASS stratification (upland/lowland). The five habitat categories with the highest densities of Canada Geese and the greatest variance in numbers were sampled. Results Between 1989 and 1999, the number of Canada Geese on land with over 5% water cover and on lowland with some water cover increased by on average 156%, an average rate of increase of 9.9% per annum. Southern Britain probably now holds a minimum of 82 000 Canada Geese. Between 1989 and 1999, the number of Greylag Geese on land with over 5% water cover and on lowland with some water cover increased by on average 214%, an average rate of increase of 12% per annum. Southern Britain probably now holds a minimum of 30 000 Greylag Geese. Conclusion Maximum densities of Canada Geese may have been reached in high-density habitats but their numbers are still increasing very rapidly. Greylag Geese are increasing even more rapidly.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".