Integrating the effects of fish exploitation and interspecific competition into current life history theories: an example with lacustrine brook trout (<i>Salvelinus fontinalis</i>) populations
Bibliographic record
Abstract
We used data from 17 populations of lacustrine brook trout (Salvelinus fontinalis) of the Canadian Shield, southern Quebec, to test whether early maturity (in males and females) and high reproductive effort (in females) are associated with increased (i) fish exploitation (sportfishing) and (ii) interspecific competition through their effects on growth and survival. The age at maturity of males and females was inversely related to the intensity of both fishing and interspecific competition. Fishing and interspecific competition affect the age at maturity through their effect on adult survival but not on growth, supporting predictions of life history models based on survival. In contrast, we did not find consistent effects of interspecific competition and fishing on the gonadosomatic index of females, which was directly related to survival (in all populations) and to the age at maturity (in exploited populations). These latter results are contrary to the predictions of life history models under the assumption that survival is directly related to growth rate. Our results suggest that reproductive effort and age at maturity are not dependent on growth when survival is independent of growth, as is the case in exploited and sympatric populations experiencing low adult survival but high growth.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".