Model-Based Predictions of the Effects of Harvest Mortality on Population Size and Trend of Yellow-Billed Loons
Why this work is in the frame
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Bibliographic record
Abstract
Yellow-billed loons (Gavia adamsii) breed in low densities in northern tundra habitats in Alaska, Canada, and Russia. They migrate to coastal marine habitats at mid to high latitudes where they spend their winters. Harvest may occur throughout the annual cycle, but of particular concern are recent reports of harvest from the Bering Strait region, which lies between Alaska and Russia and is an area used by yellow-billed loons during migration. Annual harvest for this region was reported to be 317, 45, and 1,077 during 2004, 2005, and 2007, respectively. I developed a population model to assess the effect of this reported harvest on population size and trend of yellow-billed loons. Because of the uncertainty regarding actual harvest and definition of the breeding population(s) affected by this harvest, I considered 25 different scenarios. Predicted trends across these 25 scenarios ranged from stability to rapid decline (24 percent per year) with halving of the population in 3 years. Through an assessment of literature and unpublished satellite tracking data, I suggest that the most likely of these 25 scenarios is one where the migrant population subjected to harvest in the Bering Strait includes individuals from breeding populations in Alaska (Arctic coastal plain and the Kotzebue region) and eastern Russia, and for which the magnitude of harvest varies among years and emulates the annual variation of reported harvest during 2004-07 (317, 45, and 1,077 yellow-billed loons). This scenario, which assumes no movement of Canadian breeders through the Bering Strait, predicts a 4.6 percent rate of annual population decline, which would halve the populations in 15 years. Although these model outputs reflect the best available information, confidence in these predictions and applicable scenarios would be greatly enhanced by more information on harvest, rates of survival and reproduction, and migratory pathways.
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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 | 0.001 |
| 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) | 0.000 | 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 it