Population trend status of Ontario’s forest birds
Bibliographic record
Abstract
Recent population trends of Ontario’s forest birds were assessed by integrating results across 8 bird surveys to provide an estimate of trend status for all of Ontario, and for 2 forested regions of Ontario separately. Surveys with mid- and longterm trends were relied on most extensively in this assessment. Comparison of the first and second Breeding Bird Atlases was especially important for estimating trends in northern forests, but overall reliability of status assessments in the north was considered poor due to limited coverage and significant potential for bias. Trends of most forest birds were stable or positive at the Ontario-wide scale, with trends at least as positive as forest birds elsewhere in North America, and showing more positive trends overall than birds of agricultural landscapes. Nevertheless, individual species trends ranged from large declines to large increases, and several forest birds have been added to Species at Risk lists largely because of population declines. There were few differences in trend status among forest birds grouped by habitat association or migratory guild, although all 5 aerial insectivore species have declined. Better monitoring coverage of the boreal will be needed if improved reliability of trends is desired in the near future. Key words: Ontario, forest birds, boreal forest, population trend, bird surveys, monitoring reliability
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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 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".