Recent Trends in First-Year Survival for Black Brant Breeding in Southwestern Alaska
Bibliographic record
Abstract
We estimated first-year and adult survival of Black Brant (Branta bernicla nigricans) from the Yukon—Kuskokwim Delta, Alaska, to assess (1) the role that first-year survival plays in declining recruitment and in the local breeding population's decline since the early 1980s and (2) the potential role of subsistence harvest in declining first-year survival. We used band-recovery models in program Mark to estimate band-recovery rates and annual survival from 1986 to 2007. The only models of band recoveries that received support contained annual variation and an additive effect of sex on band-recovery rates. The two best-supported models of annual survival differentiated between first-year and older Black Brant. The best-supported model (Akaike weight = 0.69) included a linear trend in first-year survival, while the second best-supported model (Akaike weight = 0.20) included an effect of mean gosling mass on first-year survival. Band-recovery rates corresponded to harvest rates of ∼1%, indicating that during the study period harvest was not demographically important. Adult survival was comparable (0.87) to that from other studies of this population, while first-year survival declined from 0.46 in 1986 to 0.24 in 2007. The trend of decline in first-year survival represented the effects of variation in conditions for goslings' growth in the breeding area combined with unknown effects on migration and in the wintering areas. Declining first-year survival is an important contributor to decline in the local breeding population of Black Brant.
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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) | 0.004 | 0.001 |
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".