Modeling spring migration patterns of scoters and loons in the Bay of Fundy
Bibliographic record
Abstract
Populations of scoter and loon species that winter in the Atlantic are understudied in North America, but coastal observatories may provide the data required to fill some of the knowledge gaps. The migration of scoters and loons has been monitored at the Point Lepreau Bird Observatory (PLBO) in the Bay of Fundy every spring since 1996, but little peer-reviewed research based on the resultant database has been published. Using data collected over 18 years at the Bay of Fundy (2000–2017), our objectives were to (1) determine the most accurate method of modeling hourly migration rates for Surf (Melanitta perspicillata), White-winged (M. deglandi), and Black (M. americana) scoters, and Red-throated (Gavia stellata) and Common (G. immer) loons, and (2) assess trends in hourly migration rates for our five focal species to determine if the numbers of migrants passing PLBO have changed over time. We calculated hourly migration rates for each of our five focal species and evaluated drivers (i.e., timing and environmental conditions) of migration and annual trends using zero-inflated generalized linear mixed models (GLMMs). We found that drivers of migration differed among species. Specifically, hourly migration rates decreased with increasing tide height for all species except Red-throated Loons. In addition, hourly migration rates increased with increasing wind vector (i.e., a tailwind) for the three scoter species, but decreased with increasing wind vector for the two loon species. Scoter migration rates peaked daily between 11:00 and 13:00 UTC, but we found no daily peak for either loon species. Peak hourly migration rates of Black and Surf scoters occurred from 12 to 26 April, but migration rates of White-winged Scoters and both loon species continued to increase throughout our migration-monitoring window. Finally, we found no changes in hourly migration rates over time for any of our focal species, suggesting no changes in abundance over the 18 years of data collection. Our study reveals the importance and utility of long-term, coastal observation stations, and we recommend their continued funding and use as valuable sources of monitoring data.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".