Changes in Regional Winter Abundance of the Golden-crowned Sparrow Revealed by Christmas Bird Count Data
Bibliographic record
Abstract
Assessing trends in abundance of bird species whose breeding range is poorly sampled by Breeding Bird Surveys poses significant challenges. The Golden-crowned Sparrow (Zonotrichia atricapilla) is one such species. Range-wide data from the Christmas Bird Count (CBC) can be used to assess trends in this species’ winter abundance and, by inference, range-wide breeding population trends. We used CBC data from throughout the winter range of the Golden-crowned Sparrow over the 40 years from 1984–2023 to assess abundance trends. Our analysis suggests that the overall population is stable, but that numbers are increasing significantly at the northern edge of the winter range, and declining significantly at the southern edge, suggesting a poleward shift in relative abundance in recent decades. Increases in winter temperatures throughout this species’ winter range may be a key driver of this northward shift either through changes in over-winter survival, breeding season productivity, or both.
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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 | 0.000 | 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 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".