Ecological mechanisms favouring behavioural diversification in the absence of morphological diversification: a theoretical examination using brook charr (<i>Salvelinus fontinalis</i>)
Bibliographic record
Abstract
1. Behavioural diversification is thought to be an important initial step in the origin of resource polymorphisms. We developed a model for young brook charr (Salvelinus fontinalis Mitchill) to examine four mechanisms that could generate a U-shaped relationship between growth rate (fitness) and the proportion of time spent moving that would favour alternative foraging tactics in the absence of obvious differences in body size and shape. 2. Recently emerged brook charr of similar size and shape inhabit still-water pools along the sides of streams. Some individuals tend to sit and wait for crustacean prey at the pool substrate near the bank, while others tend to search actively for insect prey at the pool surface away from the bank. 3. The ecological mechanisms modelled were (i) the relationship between the rate of prey capture and the proportion of time spent moving is curvilinear, such that net rate of energy gain is maximized at two different levels of activity; (ii) switching between foraging locations and, hence, tactics involves lost opportunity and travel costs; (iii) switching between prey types and, hence, tactics involves a learning cost; and (iv) foraging success is status-dependent with individuals switching between tactics having a lower status than those specializing at a tactic. 4. Singly, no mechanism predicted the U-shaped relationship between growth rate and the proportion of time spent moving. Together, a U-shaped relationship was obtained, indicating that the behavioural diversification and diversifying selection observed in the field may be a consequence of multiple, subtle mechanisms.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".