Census counts of Common Murres adjusted for timing of breeding are more accurate than counts based on calendar dates
Bibliographic record
Abstract
Abstract Climate change has resulted in a marked advancement in the breeding phenology of many bird species. Since the timing of many monitoring programs is based on calendar dates, changes in the timing of birds’ breeding seasons may result in a mismatch with the census period. Using data from a long-term population study of Common Murres (Uria aalge; Common Guillemots in Europe) on Skomer Island, Wales, together with simulations, we show that the 2-week advance in the timing of breeding in Common Murres between 1973 and 2020 has serious implications for the timing of census counts. We show that because censuses have traditionally been conducted during the same fixed calendar period each year, the size of the breeding population has been underestimated. We recommend that censuses of breeding seabirds be made relative to the median egg-laying date rather than on specific calendar dates. Since climate change has resulted in a widespread advance in the timing of birds’ breeding seasons in the northern hemisphere, our results may be relevant to Common Murres at other colonies, and to other bird species worldwide.
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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) | 0.001 | 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 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".