Survival and Recovery Rate of Canada Geese Staging in Interior Alaska
Bibliographic record
Abstract
Abstract: Lesser Canada geese ( Branta canadensis parvipes ) are indistinguishable from other subspecies of small Canada geese on the wintering grounds using current survey methods. Consequently, managers are unable to adequately measure their abundance. Without direct estimates of abundance, researchers often use estimates of vital rates that influence abundance (e.g., annual survival) to monitor potential impact of harvest on the population. Based on capture and re‐sighting data records of 567 geese marked from 1994 through 1998, we calculated annual survival and recovery rates for different age and sex classes of white‐cheeked geese staging in interior Alaska. We compared those survival and recovery rates with those of other neck‐collared white‐cheeked geese. The best approximating model allowed survival to vary by age class while holding Seber's recovery probability (r̂) constant over sex, age class, and time. We estimated annual survival to be 0.49 (SE = 0.05) for hatch‐year geese and 0.68 (SE = 0.03) for after‐hatch‐year geese based on the weighted average of all models with a change in Akaike's Information Criterion adjusted for small sample size and lack of fit < 4. Estimates of annual survival of white‐cheeked geese in this study are among the lowest and recovery estimates are among the highest for migratory populations of neck‐collared geese. Low survival estimates of Canada geese in our study suggest that harvest rates may be higher than in many other populations. Surveys to estimate abundance or other population parameters such as reproductive success and recruitment are necessary to determine whether this population is self‐sustaining. Furthermore, we recommend monitoring abundance and harvest of small white‐cheeked geese east and west of the Cascade Mountain Range separately to better determine harvest pressure on white‐cheeked geese wintering east of the Cascades.
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 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 | 0.000 | 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".