Life history and large-scale habitat use of brown trout (<i>Salmo</i><i>trutta</i>) and brook trout (<i>Salvelinus fontinalis</i>) — implications for species replacement patterns
Bibliographic record
Abstract
Simple models of temperature-mediated interference competition have generally failed to explain salmonid species replacement patterns along altitudinal gradients, a fact that emphasizes the need to link individual features and their relation to habitat characteristics to population-level dynamics. We compared life history parameters in stream-resident populations of brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta) in eight boreal streams. By use of electrofishing data from 1000 sites, we analyzed and related differences in life history traits to habitat- and interaction-related patterns of growth and densities of brook and brown trout, respectively. Brown trout were competitively dominant throughout the size span of sampled sympatric sites and lowered growth rates in sympatry were mainly caused by environmental factors, revealing a link between brook trout invasions and habitat-related limitations on brown trout performance. Still, the frequency of allopatric brook trout sites increased in the smallest watersheds, indicating that localities with a high degree of brook trout dominance rarely sustain brown trout over time. Brook trout populations had higher turnover rates and proportions of mature females than brown trout populations. Our results suggest growth potential and its effect on population fecundity as a critical factor limiting competitive ability and distribution of brown trout in Swedish brook trout dominated headwaters.
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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 | 0.000 |
| 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".