Oilfield Development and Glaucous Gull (Larus hyperboreus) Distribution and Abundance in Central Alaskan Beaufort Sea Lagoons, 1970–2001
Bibliographic record
Abstract
We evaluated aerial survey data for glaucous gulls (Larus hyperboreus) in central Alaskan Beaufort Sea lagoons near the Prudhoe Bay oilfields during June to September 1978– 2001 for trends in numbers of glaucous gulls, associations with human activity, and confounding relationships with environmental variables. Most glaucous gulls were in barrier island and mainland shoreline habitats, and the total number of gulls per survey ranged from 50 to 1600. Seasonal variation in abundance was apparent, with the largest numbers of gulls consistently recorded during September surveys. Ice cover and wave height had a significant negative correlation with the linear density of glaucous gulls (gulls/km). There was no clear trend in abundance of gulls in the lagoons at Prudhoe Bay or obvious interaction with human activity (such as air traffic, boat traffic, or humans on land or water) in the survey area during the period of oilfield development (1978–2001). We compiled glaucous gull nest counts from 1970 to 2001 across barrier islands to evaluate trends in the number of nests and associations with other colonial nesting species. The mean number of active glaucous gull nests increased from 1970–74 (77.6 nests per year) to 1975–85 (154.4 nests per year), but there was no evidence of a difference from 1970–74 to 1987– 2001 (153.0 nests per year). However, the change in 1976 from aerial to ground-based nest surveys confounds comparison of the survey periods before this date (1970– 74) with those after it (1975–85 and 1987– 2001). A strong positive relationship between the number of glaucous gull nests and both common eider and snow goose nests suggests that common environmental variables may be regulating nesting for these species.
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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".