Effect of Goose Removals on a Suburban Canada Goose Population
Bibliographic record
Abstract
Local-nesting or "resident" Canada geese (Branta canadensis) are coming into conflict with people and human activities in urban-suburban areas throughout North America. Capture and removal of molting geese, followed by translocation or euthanasia, is a simple way to reduce the number of geese in an area, but some critics of lethal goose control methods claim that other geese will quickly fill the void left when geese are removed from a problem area. To better understand the effectiveness of urban-suburban goose removal programs, we captured 591 resident geese (mostly adult birds) in suburban Rockland County, New York, during the summer molt, 2004 and 2005. The birds were transported, marked with neck and leg bands and released in a rural area approximately 320 km to the northwest. Band returns indicated that at least 46% of translocated geese were eventually harvested by hunters, most of those (52%) during the first September hunting season after release, and most (72%) were taken within 50 km of the release site. Neckband observations indicated that <10% of translocated birds returned to Rockland County, and few (<1%) moved to suburban areas near the release site. Annual molting period goose surveys throughout Rockland County from 2004- 2008 indicated that removal of geese from selected sites in Clarkstown resulted in nearly 60% fewer geese town wide for three subsequent years, and other geese did not quickly move in to replace birds that we removed. This study demonstrated that goose removal can be an effective way to reduce local goose populations in some areas for at least three years.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Evaluation of a goose removal program; wildlife management.
The study evaluates goose-removal effects on an animal population, not research itself.
Wildlife management experiment on suburban Canada goose removals; ecology and pest control.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".