Kiawah and Seabrook islands are a critical site for the <i>rufa</i> Red Knot ( <i>Calidris canutus rufa</i> )
Bibliographic record
Abstract
ABSTRACT The rufa Red Knot ( Calidris canutus rufa ) is a migratory shorebird that performs one of the longest known migrations of any bird species — from their breeding grounds in the Canadian Arctic to their nonbreeding grounds as far south as Tierra del Fuego — and has experienced a population decline of over 85% in recent decades. During migration, knots rest and refuel at stopover sites along the Atlantic Coast, including Kiawah and Seabrook islands in South Carolina. Here, we document the importance of Kiawah and Seabrook islands for knots by providing population and stopover estimates during their spring migration. We conducted on-the-ground surveys between 19 February - 20 May 2021 to record the occurrence of individually marked knots. In addition, we quantified the ratio of marked to unmarked knots and deployed geolocators on knots captured in the area. Using a superpopulation model, we estimated a minimum passage population of 17,247 knots (~41% of the total rufa knot population) and an average stopover duration of 47 days. Our geolocator results also showed that knots using Kiawah and Seabrook islands can bypass Delaware Bay and fly directly to the Canadian Arctic. Finally, our geolocators, combined with resighting data from across the Atlantic Flyway, indicate that a large network of more than 70 coastal sites mostly concentrated along the coasts of Florida, Georgia, South Carolina, and North Carolina provide stopover and overwintering habitat for the knots we observed on Kiawah and Seabrook islands. These findings corroborate that Kiawah and Seabrook islands should be recognized as critical sites in the knot network and, therefore, a conservation priority. As a result, the threats facing the sites — such as prey management issues, anthropogenic disturbance, and sea level rise — require immediate attention.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".