Multi‐scale relationships in thermal limits within and between two cold‐water frog species uncover different trends in physiological vulnerability
Bibliographic record
Abstract
Abstract 1. Critical thermal limits represent an important component of an organism's capacity to cope with future temperature changes. Understanding the drivers of variation in these traits may uncover patterns in physiological vulnerability to climate change. Local temperature extremes have emerged as a major driver of thermal limits, although their effects can be mediated by the exploitation of fine‐scale spatial variation in temperature through behavioural thermoregulation. 2. Here, we investigated thermal limits along elevation gradients within and between two cold‐water frog species (Ascaphusspp.), one with a coastal distribution (A. truei) and the other with a continental range (A. montanus). We quantified thermal limits for over 700 tadpoles, representing multiple populations from each species. We combined local temporal and fine‐scale spatial temperature data to quantify local thermal landscapes (i.e., thermalscapes), including the opportunity for behavioural thermoregulation. 3. Lower thermal limits for either species could not be reached experimentally without the water freezing, suggesting that cold tolerance is <0.3°C. By contrast, upper thermal limits varied among populations, but this variation only reflected local temperature extremes inA. montanus, perhaps as a consequence of the greater variation in stream temperatures across its range. Lastly, we found minimal fine‐scale spatial variability in temperature, suggesting limited opportunity for behavioural thermoregulation and thus increased vulnerability to warming for all populations. 4. By quantifying local thermalscapes, we uncovered different trends in the relative vulnerability of populations across elevation for each species. InA. truei, physiological vulnerability decreased with elevation, whereas inA. montanus, all populations were equally physiologically vulnerable. These results highlight how similar environments can differentially shape physiological tolerance and patterns of vulnerability of species, and in turn impact their vulnerability to future warming.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".