Hotspots in cold seas: The composition, distribution, and abundance of marine birds in the North American Arctic
Bibliographic record
Abstract
The distribution and thickness of sea ice in the Arctic is changing rapidly, resulting in changes to Arctic marine ecosystems. Seabirds are widely regarded as indicators of marine environmental change, and understanding their distribution patterns can serve as a tool to monitor and elucidate biological changes in the Arctic seas. We examined the at-sea distribution of seabirds in the North American Arctic in July and August, 2007–2012, and marine areas of high density were identified based on bird densities for four foraging guilds. Short-tailed shearwaters (Puffinus tenuirostris) were the most abundant species observed. Northern fulmars (Fulmarus glacialis), thick-billed murres (Uria lomvia), and dovekies (Alle alle) were also sighted in large numbers. Few birds were sighted between Dolphin and Union Strait and King William Island. Areas of high density over multiple years were found throughout the entire western portion of the study area (Bering Sea, Bering Strait, and Chukchi Sea), Lancaster Sound, Baffin Bay, Davis Strait, and the low Arctic waters off Newfoundland. These waters are characterized by high primary productivity. This study is the first to document the marine distribution of seabirds across the entire North American Arctic within the same time period, providing a critical baseline for monitoring the distribution and abundance of Arctic seabirds in a changing Arctic seascape.
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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 | 0.000 |
| 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 | 0.000 |
| 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".