Spatial and temporal variation in harvest probabilities for American black duck
Bibliographic record
Abstract
Assessing spatial variation in waterfowl harvest probabilities from banding data is challenging because reporting and recovery probabilities have distinct spatial patterns that covary temporally with harvesting regulations, hunter effort, and reporting methods. We analyzed direct band recovery data from American black ducks banded on the Canadian breeding grounds from 1970 through 2010. Data were registered to a 1-degree grid and analyzed using hierarchical logistic regression models with spatially correlated errors to estimate the annual probabilities of band recovery and the proportion of individuals recovered in Canada. Probability of harvest was estimated from these values, in combination with independent estimates of reporting probabilities in Canada and the USA. Model covariates included estimates of hunting effort and factors for harvest regulation and band reporting methods. Both the band recovery processes and the proportion of individuals recovered in Canada had significant spatial structure. Recovery probabilities were highest in southern Ontario, along the Saint Lawrence River in Quebec, and in Nova Scotia. Black ducks breeding in Nova Scotia and southern Quebec were harvested predominantly in Canada. Recovery probabilities for juveniles were correlated with hunter effort, while the adult recoveries were weakly correlated with the implementation of stricter harvest regulations in the early 1980s. Mean harvest probability decreased in the northern portion of the survey area but remained stable or even increased in the south. Harvest probabilities for juveniles in 2010 exceeded 20% in southern Quebec and the Atlantic provinces. Our results demonstrate fine-scale variation in harvest probabilities for black duck on the Canadian breeding ground. In particular, harvest probabilities should be closely monitored along the Saint Lawrence River system and in the Atlantic provinces to avoid overexploitation.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".