Freshwater fishes maintain multi‐trait phenotypic stability across an environmental gradient in aqueous calcium
Bibliographic record
Abstract
Reductions in a limiting nutrient might be expected to necessitate compromises in the functional traits that depend on that nutrient; yet populations existing in locations with low levels of such nutrients often do not show the expected degradation of functional traits. Indeed, logperch (Percina caprodes), pumpkinseed sunfish (Lepomis gibbosus) and yellow perch (Perca flavescens) residing in low-calcium water in the Upper St. Lawrence River were all previously found to maintain levels of scale calcium comparable to those of conspecific populations in high-calcium water. Yet it remains possible that the maintenance of one functional trait (i.e., scale calcium) under nutrient-limited (i.e., low calcium) conditions could come at the expense of maintaining other functional traits that depend on the same nutrient. The present study therefore examines other calcium-dependent traits, specifically skeletal element sizes and bone densities in the same fish species in the same area. Using radiographs of 101 fish from the three species across four locations (two in high-calcium water and two in low-calcium water), this new work documents multi-trait "homeostasis" along the gradient of water calcium. That is, no effect of calcium regime (low-calcium vs. high-calcium) was detected on any of the measured variables. Further, effect sizes for the skeletal traits were very low - lower even than effect sizes previously documented for scale calcium. These results thus show that native fishes maintain phenotypic stability across a suite of functional traits linked to calcium regulation, perhaps pointing to an "organismal-level homeostasis" scenario rather than a "trait-level homeostasis" scenario.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".