Synchronization of seasonal acclimatization and short‐term heat hardening improves physiological resilience in a changing climate
Bibliographic record
Abstract
Abstract Animal survival and species distribution in the face of global warming and increasing occurrences of heatwave largely depend on how heat tolerance shifts with plastic responses at different spatiotemporal scales, including long‐term acclimation/acclimatization and short‐term heat hardening. However, knowledge about the interaction of these plastic responses is still unclear. To understand how plastic responses at different time‐scales work together to adjust heat tolerance of organisms, we examined the effect of heat hardening on the upper thermal limits of an intertidal mudflat bivalve, the razor clam Sinonovacula constricta , for different seasons using heart rate as a proxy. We observed a stronger heat hardening response of S. constricta in warm seasons, implying that heat hardening worked synchronously with seasonal acclimatization to increase resistance of the clams to high temperatures in warm seasons. In warm seasons, heat hardening increased heat tolerance by 2–4°C and showed a 24‐hr temporal dependence, suggesting an adaptation to the diel fluctuation of thermal regimes in summer. Furthermore, thermal stress resembling seasonal maximum environmental temperature induced stronger heat hardening effects, indicating that heat hardening is an essential plastic response to extreme hot weather, complementing seasonal acclimatization. Our results suggest that high temperature risk can be alleviated jointly by seasonal acclimatization and heat hardening, and emphasize the importance of considering physiological plasticity on both long‐term and short‐term temporal scales in evaluating and forecasting vulnerability of organisms to climate change. A free Plain Language Summary can be found within the Supporting Information of this article.
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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) | 0.001 | 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 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".