The effect of lake morphometry on thermal habitat use and growth in Arctic charr populations: implications for understanding climate‐change impacts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Oxygen stable isotope temperature reconstruction methods were used to estimate mean experienced summer temperatures from growth zones within individual Arctic charr otoliths sampled from lakes with contrasting morphologies but proximate locations. For either lake, otolith‐estimated temperatures were not significantly related to back‐calculated growth. Fish in the smaller lake evidenced an increase in growth with age related to increasing use of cooler thermal habitats, with the use of thermal habitat possibly governed by predation risks. No relationships between age, growth or temperature were observed in the larger lake. Significant negative effects on back‐calculated growth were observed due to increasing air temperatures in the smaller and shallower lake, possibly owing to warmer surface and littoral waters and a limited amount of preferred cool‐water habitat. A similar relationship was not observed in the larger and deeper lake and indicated that resident Arctic charr were not as vulnerable to the impacts of temperature warming, possibly because of better behavioural thermoregulation opportunities in the cooler, deeper lake. Results provide evidence for differing climate‐influenced growth outcomes among proximately located populations, with outcomes likely to depend on the differences among habitats, including lake size and morphometry which may act to influence fish densities in available preferred thermal habitats.
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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) | 0.000 | 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 it