Demographic Parameters of Rural and Urban Adult Resident Canada Geese in Georgia
Bibliographic record
Abstract
ABSTRACT In many urban metropolitan areas, resident Canada goose ( Branta canadensis ) populations have grown to nuisance levels in spite of increasing harvest opportunity. To document differences in demographic parameters between urban and rural geese, I estimated probabilities of survival, recapture, recovery, and fidelity for adult resident Canada geese between 2001 and 2006 using banding, live recapture, and dead recovery data from 2 distinct banding locations in Georgia, USA. Adult survival rates were higher for urban geese (0.958, SE = 0.020) than for rural geese (0.682, SE = 0.049). Using estimated recovery probabilities of 0.505 (SE = 0.107) for urban and 0.463 (SE = 0.045) for rural geese, along with current estimates of crippling loss and reporting rate, the estimated mean harvest rate for urban geese was 0.029 (SE = 0.006) and for rural geese was 0.202 (SE = 0.020). Fidelity rates were similar between urban (0.730, SE = 0.033) and rural geese (0.713, SE = 0.069). This information suggests that urban segments of the Canada goose population have substantially higher survival than rural geese and are harvested at a very low rate, and that liberalizing hunting regulations may have little impact on Georgia's urban goose population. Wildlife managers may need to consider options other than sport hunting to control nuisance goose populations in urban areas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".