Long-term monitoring of Arctic coastal ecology at the East Bay Mainland Research Station, in Qaqsauqtuuq Migratory Bird Sanctuary, Nunavut
Bibliographic record
Abstract
We provide an overview of 25 years of research at the East Bay Mainland Research Station, in the Qaqsauqtuuq Migratory Bird Sanctuary, Southampton Island, Nunavut. The earliest research at the site targeted waterfowl and seabirds, but work since 2000 has focused on shorebirds. The site offers the longest running study of breeding shorebirds in the Canadian Arctic, with more than 1800 nests of 12 species monitored. Monitoring at this site has contributed to our understanding of the breeding ecology of shorebirds, including factors influencing timing of laying, habitat selection, and breeding success. Research has also contributed to knowledge of shorebird ecology throughout the annual cycle, through international collaborations using cutting-edge tracking technologies and novel analytic methods. Importantly, long-term monitoring data have provided opportunities to evaluate demographic shifts in shorebird species and communities in relation to changing climate and threats throughout the annual cycle. We recorded 75 bird species and 9 mammal species at the site, and confirmed breeding for 30 bird species. Additionally, research and training activities at East Bay Mainland have made important contributions to capacity for Inuit self-determination in Arctic environmental monitoring, and have supported the development of international commitments and policies around species conservation and management.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".