Limited plasticity but increased variance in physiological rates across ectotherm populations under climate change
Bibliographic record
Abstract
Abstract Climate change causes warmer and more variable temperatures globally, impacting physiological rates and function in ectothermic animals. Acclimation of physiological rates can help maintain function. However, it is unresolved how variance in physiological rates changes with temperature despite its potential ecological and evolutionary importance. We developed new effect sizes that capture how both the mean and variation in physiological rates change across temperature (based on the temperature coefficient, ) and used them to test how acclimation and acute thermal responses vary across aquatic and terrestrial ectotherms using meta‐analysis (>1900 effects from 226 species). Comparing both the magnitude of acclimation and changes in variation side‐by‐side provides unique opportunities for evaluating the importance of plasticity and selection under climate change. We show that variance in physiological rates increases at higher temperatures, but that the magnitude of change depends on habitat. Freshwater and marine ectotherms are capable of acclimation and have the greatest increase in variance. In contrast, terrestrial ectotherms have reduced acclimation abilities and smaller increases in physiological rate. Simulations suggest that these patterns may result from differences in among‐individual variation in thermal breadth and optima of performance curves across habitats. Our results highlight the greater vulnerability of terrestrial ectotherms to climate change because of both a lack of acclimation capacity and a limited increase in variance that may provide less raw material for evolutionary adaptation. Considering both acclimation capacity and variance in physiological rates side‐by‐side is therefore important for understanding how climate change will impact populations. Read the free Plain Language Summary for this article on the Journal blog.
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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) | 0.002 | 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".