Survey trends of North American shorebirds: population declines or shifting distributions?
Bibliographic record
Abstract
We analyzed data from two surveys of fall migrating shorebirds in central and eastern North America to estimate annual trends in means per survey and to determine whether trends indicate a change in population size or might have been caused by other factors. The analysis showed a broad decline in means per survey in Atlantic Canada and the northeastern United States (North Atlantic region). For example, 9 of 9 significant trends in this region were <1 (P=0.004), and the mean, annual rate of change among 30 species was 0.9783, a decline of −2.17% per year (P<0.001). Trends in the midwestern United States (Midwest region) showed no clear pattern. The mean among 29 species was 1.0090 (P=0.35). Only 4 of the trends were significant. Several hypotheses were evaluated to identify causes of the declining means per survey in the North Atlantic region. The most likely hypothesis appears to be a decline in the breeding populations that supply migrants to the North Atlantic region, but a change in movements, for example passing through the region more quickly in recent years, cannot be excluded as an explanation. Further surveys of arctic breeding areas coupled with analysis of long‐term survey data from western North America would be helpful in determining whether the declines found in this analysis are also occurring in other areas.
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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 | 0.003 |
| 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 | 0.001 |
| 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".