Abundance, production, and migrations of nesting green turtles at Rose Atoll, American Samoa, a regionally important rookery in the Central South Pacific Ocean
Bibliographic record
Abstract
Sea turtles are a taxon of conservation concern and are highly migratory, exposing them to a variety of threats (e.g., fisheries bycatch, direct harvest) across their lifetime. Understanding the abundance of nesting females, hatchling production, and migratory movements - three of the most basic biological data needs for this species group - is imperative for population assessment. This study summarizes novel data most relevant to population assessments of the endangered central south Pacific (CSP) green turtle ( Chelonia mydas ) population, determined from annual rapid assessment surveys (mean survey duration=7.6 days year -1 , n=61 survey days over 8 nesting seasons) and satellite telemetry at Rose Atoll, American Samoa, from 2012 to 2019. A minimum of 138 unique females nested in the Rose Atoll National Wildlife Refuge (RANWR) over the study period with 218 total females observed. Satellite tracks of post-nesting females suggest Fiji (n=33/48, 70.2%) is the primary foraging ground for turtles nesting at RANWR, though other areas throughout the south Pacific Ocean are also important. Limited data suggest hatchling production was high (average hatching success=92.3%) and nest temperature data collected from 2017-2019 suggest primary sex ratios were likely balanced during this time. These are positive signs for the resilience of this nesting population, but climate change poses threats to RANWR and other low-lying tropical islands throughout the central south Pacific, as nesting areas are potentially exposed to beach erosion, tidal inundations, and increasing temperatures leading to sex bias and embryonic death.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".