Importance of the National Petroleum Reserve–Alaska for Aquatic Birds
Bibliographic record
Abstract
We used data from aerial surveys (1992-2010) of >100,000 km(2) and ground surveys (1998-2004) of >150 km(2) to estimate the density and abundance of birds on the North Slope of Alaska (U.S.A.). In the ground surveys, we used double sampling to estimate detection ratios. We used the aerial survey data to compare densities of birds and Arctic fox (Vulpes lagopus), the major nest predator of birds, on the North Slope, in Prudhoe Bay, and in nearby areas. We partitioned the Prudhoe Bay oil field into 2 × 2 km plots and determined the relation between density of aquatic birds and density of roads, buildings, and other infrastructure in these plots. Abundance and density (birds per square kilometer) of 3 groups of aquatic birds-waterfowl, loons, and grebes; shorebirds; and gulls, terns, and jaegers-were highest in the National Petroleum Reserve-Alaska (NPRA) and lowest in the Arctic National Wildlife Refuge. Six other major wetlands occur in the Arctic regions of Canada and Russia, but the largest population of aquatic birds was in the NPRA. Aquatic birds were concentrated in the northern part of the NPRA. For example, an area that covered 18% of the NPRA included 53% of its aquatic birds. The aerial surveys showed that bird density was not lower and fox density was not higher in Prudhoe Bay than in surrounding areas. Density of infrastructure did not significantly affect bird density for any group of species. Our results establish that the NPRA is one of the most important areas for aquatic birds in the Arctic. Our results and those of others also indicate that oil production, as practiced in Prudhoe Bay, does not necessarily lead to substantial declines in bird density or productivity in or near the developed areas. Prioridades para la Conservación de Aves en el Norte de Alaska.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".