A Comparison of Constant-effort Mist Netting Results at a Coastal and Inland New England Site during Migration
Bibliographic record
Abstract
We compared population trends from spring and fall migration capture data from two constant-effort banding stations in New England: one coastal (Manomet Center for Conservation Sciences, hereafter Manomet) and one inland (Vermont Institute of Natural Science, VINS). Data were examined for two time periods, 1981-1992 and 1986-1992. Twelve-year population trends were compared to regional Breeding Bird Survey (BBS) data for the same period. The two migration data sets showed little congruence. Of 22 species examined, Manomet data showed significant declines in 11 during one or both seasons, whereas seven species increased significantly at VINS. The number of significant trends at both sites increased between a 7-year and a 12-year sample. Among six species that were strictly transient at the two sites, five showed the same 12-year trend in fall. In general, Manomet tracked BBS data from the Northern Spruce-Hardwood region reasonably well, while VINS more closely tracked BBS trends from Northern New England. Neither site correlated well with BBS trends from Quebec. VINS captured significantly higher proportions of adult birds than did Manomet in 81% of species examined. However, the two sites tracked trends in age ratios largely independently. Several factors appeared to account for the weak congruence between sites, and we discuss the limitations in comparing these two data sets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".