Using Long-Term Constant-Effort Banding Data to Monitor Population Trends of Migratory Birds: A 33-Year Assessment of Adjacent Coastal Stations
Bibliographic record
Abstract
One technique for monitoring population trends of many species of migratory songbirds is to assess changes in population indices at constant-effort mist-netting stations located at sites of migration stopover. However, few studies have attempted to validate this approach. We compared long-term (1969–2001) population trends based on annual variation in capture rates at two banding stations located 30 km apart in southern Rhode Island, with one on the mainland, the other on an offshore island. Of 24 species with sufficient sample sizes, 21 species exhibited a significant linear decline at one or both stations. There was a high degree of conformity in trend-slope directions observed at each station. Annual fluctuations and trend magnitude conformed less well, although there was more concordance for nine transient species that do not breed in southern New England. At both stations trends were similar to those at a migration-monitoring station ∼95 km away in coastal Massachusetts. The trends at this network of three migration-monitoring stations were more negative than those of Breeding Bird Surveys in northern New England and southeastern Canada. Our results demonstrate that constant-effort mist-netting stations could be used to monitor population trends of many species of migratory songbirds, although it is not clear which breeding populations are being monitored. This suggests that banding stations could be used to supplement existing large-scale monitoring programs.
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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".