Modeling Movement and Fidelity of American Black Ducks
Bibliographic record
Abstract
Spatial relationships among stocks of breeding waterfowl can be an important component of harvest management. Prediction and optimal harvest management under adaptive harvest management (AHM) requires information on the spatial relationships among breeding populations (fidelity and inter-year exchange), as well as rates of movements from breeding to harvest regions. We used band-recovery data to develop a model to estimate probabilities of movement for American black ducks (Anas rubripes) among 3 Canadian breeding strata and 6 harvest regions (3 in Canada, and 3 in the United States) over the period 1965–1998. Model selection criteria suggested that models containing area-, year-, and age-specific recovery rates with area- and sex-specific movement rates were the best for modeling movement. Movement by males to southern harvest areas was variable depending on the originating area. Males from the western breeding area predominantly moved to the Mississippi Flyway or southern Atlantic Flyway (Ψij = 0.353, SE = 0.0187 and Ψij = 0.473, SE = 0.037, respectively), whereas males that originated in the eastern and central breeding strata moved to the northern Atlantic flyway (Ψij = 0.842, SE = 0.010 and Ψij = 0.578, SE = 0.0222, respectively). We used combined recoveries and recaptures in Program MARK to estimate fidelity to the 3 Canadian breeding strata. Information criteria identified a model containing sex- and age-specific fidelity for black ducks. Estimates of fidelity were 0.9695 (SE = 0.0249) and 0.9554 (SE = 0.0434) for adult males and females, respectively. Estimates of fidelity for juveniles were slightly lower at 0.9210 (SE = 0.0931) and 0.8870 (SE = 0.0475) for males and females, respectively. These models have application to the development of spatially stratified black duck harvest management models for use in AHM.
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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".