Origins and characteristics of Nearctic landbirds in Britain and Ireland in autumn: a statistical analysis
Bibliographic record
Abstract
We used data from eastern North America in regressions to explain autumn frequencies of Nearctic landbird species in Britain and Ireland (UK‐IR). The data were: day‐counts of 16 August–15 November from Nova Scotia (NS) on Sable Island 1963–2000 and Seal Island (1963–2002), combined in half‐monthly intervals to account for seasonality; published seasonal totals (10‐ to 11‐day intervals, 20 August–10 November 1955–80) of birds killed at a Florida (FL) TV tower; and published counts following a ‘Fallout’, 11 October 1998, of unseasonal species and southern vagrants in NS, believed to have originated as migrants in the southeast USA that followed a cold front offshore into strong southwest flow beyond. We also used the following species variables: body mass and wing length for size; sd of mass as a proxy for lipid capacity; a five‐level index of migratory span (1 for within North America to 5 for almost totally to South America); latitude of easternmost breeding, and distance to nearest normal range to indicate status in NS; a two‐level index for day vs. night migrants; an index, where pertinent, of significant population change (0 and 2 for a decrease and increase, respectively, 1 for no change). We also used classification and regression trees to cluster the potential transatlantic vagrants into homogeneous groups based on the explanatory variables. Standard generalized linear model regressions using counts from NS islands and FL produced highly positively skewed residuals (many species too common in UK‐IR), but robust regressions eliminated statistical problems, and strengthened effects of non‐count variables. Results using Fallout records, representing a subset of longer‐distance night migrants, were statistically acceptable. The Fallout list, when supplied with counts from the same species from the NS islands and FL, produced highly significant (R2 = 0.79–0.93) and statistically acceptable regressions that were not improved by robust versions. Overall, the results indicate that October counts, especially of generally larger, longer‐distance migrants, best represented those reaching UK‐IR. The effect of geographical remoteness was negative – vagrants in NS were less likely to appear in UK‐IR. Population changes were important in predicting the 1956–2003 UK‐IR counts from 1955–80 FL counts. The seasonal characteristics, high explanatory power of the Fallout list and over‐representation of probable over‐ocean migrants in the standard regressions all support suggestions by others that many Nearctic vagrants in UK‐IR originate in flights off southeast USA and are displaced downwind across the North Atlantic.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".