Extreme thermal fluctuations from climate change unexpectedly accelerate demographic collapse of vertebrates with temperature-dependent sex determination
Bibliographic record
Abstract
Abstract Global climate is warming rapidly, threatening vertebrates with temperature-dependent sex determination (TSD) by disrupting sex ratios and other traits. Less understood are the effects of increased thermal fluctuations predicted to accompany climate change. Greater fluctuations could accelerate feminization of species that produce females under warmer conditions (further endangering TSD animals), or counter it (reducing extinction risk). Here we use novel experiments exposing eggs of Painted Turtles ( Chrysemys picta ) to replicated profiles recorded in field nests plus mathematically-modified profiles of similar shape but wider oscillations, and develop a new mathematical model for analysis. We show that broadening fluctuations around naturally male-producing (cooler) profiles feminizes developing embryos, whereas embryos from warmer profiles remain female or die. This occurs presumably because wider oscillations around cooler profiles expose embryos to very low temperatures that inhibit development, and to feminizing temperatures where most embryogenesis accrues. Likewise, embryos incubated under broader fluctuations around warmer profiles experience mostly feminizing temperatures, some dangerously high (which increase mortality), and fewer colder values that are insufficient to induce male development. Therefore, as thermal fluctuations escalate with global warming, the feminization of TSD turtle populations could accelerate, facilitating extinction by demographic collapse. Aggressive global CO 2 mitigation scenarios (RCP2.6) could prevent these risks, while intermediate actions (RCP4.5 and RCP6.0 scenarios) yield moderate feminization, highlighting the peril that insufficient reductions of greenhouse gas emissions pose for TSD taxa. If our findings are generalizable, TSD squamates, tuatara, and crocodilians that produce males at warmer temperatures could suffer accelerated masculinization, underscoring the broad taxonomic threats of climate change.
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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 | 0.000 | 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) | 0.001 | 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".