Bibliographic record
Abstract
Abstract. A predictive ecological response to both the present and past climate crises is that marine ectotherm species will become smaller before going extinct or fluctuate in abundance and size with environmental conditions. The problem with studying past climate events with high rates and magnitude of warming, which may serve as analogues for projected climate change, is that very few species, or even genera, survived such events. Here, we utilized one of the few records of marine bivalves that spans the Permian–Triassic climate crisis with specimen-level data and at a high resolution. These measurements come from the Bellerophon and Werfen formations of the Dolomites in Italy, representing relatively shallow marine environments. At the species-level, there is almost a complete turnover, and the newly evolved species are typically significantly smaller, but not unusually small, whereas the three surviving species do not show a significant body size change. Our results clarify that the observed temporary size reduction at the genus-level is primarily driven by the preferential evolution of smaller species after the extinction, rather than, as often assumed, by a size decrease within existing species; this challenges the universal validity of the 'Lilliput effect' in the sense of direct intra-species dwarfing, but confirms it as a consequence of faunal turnover. Subsequently, there are two pulses of genus-level body size recovery determined by different mechanisms. The first phase (late Griesbachian) is driven by the size-increase of the existing species, whereas the second phase (early Spathian) is also due to the evolution of larger species. The effects of abiotic and biotic factors in controlling these body size dynamics are superimposed during the Early Triassic. These results suggest a mechanism to explain size reductions during climate crises, but does not find a species-level body size reduction to be a forecastable response to extreme climate warming.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.773 | 0.654 |
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".