Latitudinal variation in growth and otolith‐inferred field metabolic rates of Canadian young‐of‐the‐year Arctic charr
Bibliographic record
Abstract
Abstract Countergradient variation (CGV) is defined as genetic variation that counteracts the negative influences of the physical environment, minimising phenotypic variability along an environmental gradient. CGV is thought to have relevance in predicting the response of organisms to climate variability and change. To test the hypothesis that growth rate increased with latitude, consistent with CGV, young‐of‐the‐year (YOY) Arctic charr, Salvelinus alpinus, were examined along a ~27° latitudinal gradient in central and eastern Canada. Growth rates were estimated from fork lengths standardised by the thermal opportunity for growth based on experienced water temperatures derived using otolith oxygen stable isotopes. Results demonstrated patterns consistent with CGV, where northern populations demonstrated faster growth rates. A secondary aim was to test for similar geographical patterns in otolith‐inferred metabolic rates, which reflect the energetic costs of standard metabolic rate (SMR) and other processes such as feeding, locomotion, thermoregulation, reproduction and growth. Results demonstrated a significant, positive relationship between otolith‐inferred metabolic rate and latitude, which may reflect an increase in one, or a combination, of the above‐noted physiological processes. The similar latitudinal pattern in growth and otolith‐inferred metabolic rates suggests greater intake of food per unit of time by northern fish. The phenotypic variation in physiological traits observed here demonstrates the significant adaptability of Arctic charr to different thermal regimes with different growing season lengths. Determining the relative contributions of phenotypic plasticity and genetic variation to the observed latitudinal variation will be critical to predicting the responses of Arctic charr to climate change more accurately.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".