Alternative forms of brook trout nest site selection alter modeled offspring thermal experience and emergence phenology in groundwater-influenced streambeds
Bibliographic record
Abstract
Although incubation temperature strongly influences salmonid phenotypic variation, few studies have considered the effect of competition on nest site selection and the resultant embryonic thermal experience. We combined field observations and simulations of brook trout ( Salvelinus fontinalis) spawning across a groundwater-induced thermal mosaic to assess whether habitat selection could alter spawning patch-level offspring thermal experience. We first assessed whether wild brook trout exhibited spawning behaviors consistent with competition for limited habitat. Given a fixed thermal habitat template, we then simulated offspring incubation temperature and temperature-dependent emergence timing following random, observed, and purely size-structured habitat selection scenarios. Brook trout generally selected warmer nest locations, but temperatures varied widely (1.8–8.1 °C) due in part to competition-related behaviors: minimum nest temperatures declined as breeder density increased, larger fish used warmer nests, and nest reuse frequency increased with nest temperature. Consequently, the three habitat selection scenarios generated biologically meaningful differences in simulated patch-level incubation temperatures and emergence dates. Studies evaluating the phenotypic and phenological consequences of incubation temperature may therefore benefit from considering alternative nesting behaviors that may substantially influence offspring thermal experience within populations.
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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 | 0.000 | 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) | 0.001 | 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".