Stopover Ecology of Red Knots in Southwestern James Bay During Southbound Migration
Bibliographic record
Abstract
ABSTRACT Many shorebirds rely on small numbers of staging sites during long annual migrations. Numerous shorebird species are declining and understanding the importance of these staging sites is important for successful conservation. We surveyed endangered rufa red knots (Calidris canutus rufa) staging in James Bay, Ontario, Canada, during southbound migration in 2017 and 2018. We used mark‐resight data and count data in an integrated Bayesian analysis to quantify migration phenology, estimate passage population size, and model the age structure of the stopover population. Many adult red knots arrived in James Bay in a single wave in early August in 2017, whereas adult red knots arrived in multiple smaller waves in July and mid‐August in 2018. These waves may correspond with breeding phenology where more red knots bred successfully and arrived in one large event in 2017 and the higher number of earlier arrivals in July 2018 may have been failed breeders. We included a binomial generalized linear model in the integrated analysis to estimate that 20% and 10% of staging red knots were juveniles in 2017 and 2018, respectively. In future applications, this method could provide a metric to assess breeding performance and develop our understanding of its role in population declines. Overall, we estimated that up to 23% of the estimated rufa red knot population staged in southwestern James Bay for an average of 10–12 days. The region is a key staging site for endangered red knots and could be included in conservation planning. © 2021 The Wildlife Society.
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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 | 0.001 | 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".