Ancient Murrelet Synthliboramphus Antiquus Colony Attendance at Langara Island Assessed Using Observer Counts and Radar in Relation to Time and Environmental Conditions
Bibliographic record
Abstract
MAJOR, H.L. 2016.Ancient Murrelet Synthliboramphus antiquus colony attendance at Langara Island assessed using observer counts and radar in relation to time and environmental conditions.Marine Ornithology 44: 233-240.The decision to attend a colony on any given day or night is arguably the result of a trade-off between survival and reproductive success.It is often difficult to study this trade-off, as monitoring patterns of colony attendance for nocturnal burrow-nesting seabirds is challenging.Here, I 1) examined the effectiveness of monitoring Ancient Murrelet colony arrivals using marine radar, and 2) evaluated differences in colony attendance behavior in relation to time, light, and weather.I found a strong correlation between the number of Ancient Murrelets counted by observers in the colony and the number of radar targets counted, with estimated radar target counts being ~95 times higher than observer counts.My hypothesis that patterns of colony attendance are related to environmental conditions (i.e.light and weather) and that this relationship changes with time after sunset was supported.The top supported model included interactions between time after sunset and light and weather variables, suggesting that they were important predictors of colony arrivals.Contrary to my prediction, results suggest that light conditions (moon absence and cloud cover) and wave height were most important for individuals arriving three hours after sunset (when >75% of arrivals would be breeders).Assuming the majority of birds arriving early in the night are breeders and those arriving late in the night are non-breeders, these results suggest differences in patterns of colony attendance that may be attributed to age and/or breeding status.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".