A phenological shift to save the boys? Current and projected trends of hatchling sex ratio of the loggerhead turtle Caretta caretta at Dalyan Beach, Türkiye
Bibliographic record
Abstract
Dalyan beach, Mugla, Türkiye hosts one of the largest loggerhead turtle rookeries in the Mediterranean. The sex of marine turtles, like many reptile species, is influenced by incubation temperature, with the threat of climate change looming increasing temperatures across the world may lead to an imbalance in the sex ratio of turtle populations. Over a ten-year study period (2012-2021), temperature dataloggers (n = 497) were placed during or the morning after ovipositioning. Using middle third of incubation as a proxy for the thermosensitive period and subsequent application of the Hill Equation, this study estimates the current and projected cohort sex ratios for Dalyan beach. The estimated overall male ratio over the ten-year study period was 25.7 % ± 23.3, with considerable interannual variation when data were compared from overlapping dates. Using the observed data, a GAM was built to predict nesting temperature using archived climate data, which explained 66.7 % of the variance. This model was applied to future projections of temperature using IPCC climate change scenario SSP 3-7.0, which resulted in a significant decrease in male ratio compared in the near term (2021-2040) 17.2 % ± 0.6 s d, mid-term (2041-2060) 14 % ± 0.5 s d and far term (2081-2100) 10.7 %. A hypothetical 10-day shift of nesting phenology would quell the effects of warming and maintain or increase current male ratio in the near term 25.6 % ± 0.8 s d. A 20-day shift would have the same effect in the near term (37.3 % ± 0.9 s d) and mid-term (31.4 % ± 0.9 s d) projections. These nesting grounds are important to the sustained survival of the species and while this study indicates restorative potential to the sex imbalance, a reliance on the development of such a phenological shift is less than favourable. While climate change projections vary between models, a situation that gives enough buffering time is unlikely, and feminisation of the population seems inevitable without further action.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".