Deciphering lifelong thermal niche using otolith δ<sup>18</sup>O thermometry within supplemented lake trout (<i>Salvelinus namaycush</i>) populations
Bibliographic record
Abstract
Abstract The selection of thermal habitat by fish is strongly regulated by physiology and behaviour. However, delineation of a species lifelong thermal niche remains technically challenging. Lake trout ( Salvelinus namaycush ) survival and productivity are recognised as being tightly linked to a somewhat restricted thermal habitat. The factors guiding temperature selection during each life stage remain poorly understood. In this study, we tested the significant factors controlling the realised thermal niche of lake trout from two southern Quebec small boreal lakes that experienced supplementation stocking during the last 20 years. We used oxygen stable isotope (δ 18 O) thermometry of otolith calcium carbonates (aragonite) using secondary‐ion mass spectrometry to estimate experienced lifelong temperatures. We investigated the thermal habitat of lake trout with known genotypes (local, hybrid, and stocked). Ontogeny and genetic origin influenced temperature selection in both studied lake trout populations. Young‐of‐the‐year consistently used warmer, shallower habitats (10.7 ± 2.6°C, 7.5 m depth) prior to a juvenile transition to colder and deeper waters (8.5 ± 3.3°C, 10 m depth). Stocked lake trout, originating from a genetically distinct ecotype, exhibited a more variable thermal niche, with some individuals consistently using warmer habitat (10.4 ± 1°C) than local fish. Their hybrid progeny also occupied a warmer thermal niche, intermediate to the parental strains. We propose that increased fat content and genetic origin are potential explanatory factors for warmer temperature use. This study reiterates that high‐resolution otolith δ 18 O thermometry is a uniquely well‐suited approach for unravelling the multiple factors that influence lifelong temperature selection in fish. Our results illustrate that the realised thermal niche is influenced by a genetic–environment interaction.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".