Black Bass Diversity: Multidisciplinary Science for Conservation
Bibliographic record
Abstract
Abstract.—Long-term studies in Ontario, Canada on Largemouth Bass Micropterus salmoides and Smallmouth Bass M. dolomieu have demonstrated that angling nesting males (both catch and harvest and catch and release) can have negative impacts on the reproductive success for the captured individual. They have also demonstrated that within a population, the male bass that provide the best and longest parental care for their offspring are the most capable of having the greatest relative contribution to the year-class. Furthermore, those males are also the most aggressive toward potential brood predators and, hence, the most vulnerable to angling. Based on those relationships, we postulated that angling in general, and especially angling for nesting bass, results in selection against aggressive individuals in a population, and as a result, the angled population evolves to become less aggressive, containing males with diminished parental care attributes, an example of fisheries-induced evolution (FIE). We recognize, however, that some change towards less aggressive behaviors may also result from learning and phenotypic plasticity. Controlled, long-term selective breeding experiments over 30+ years have, however, documented the heritability of vulnerability of bass to angling and, hence, the potential for selection to act on that trait. Reproductive competition experiments further demonstrated that the highly vulnerable strain of bass produced in those selective breeding experiments indeed had greater reproductive success than the less vulnerable strain. Because angling for Largemouth Bass has been occurring for decades, we also postulated that there should be some evidence in the wild of this FIE. In fact, we did find that the level of vulnerability to angling of nesting male Largemouth Bass in lakes that have had little to no exploitation was significantly greater than that observed for nesting males in moderately and heavily angled 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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.042 | 0.003 |
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".