Comparative Behavior of Wild Bluegill Captured Inside and Outside of a Long‐Standing Aquatic Protected Area
Bibliographic record
Abstract
Abstract In recreational fisheries it is understood that individual fish that exhibit bolder personality traits have a tendency to be removed from the population (i.e., fishing mortality via harvest or catch‐and‐release mortality), while more timid individuals remain. The use of aquatic protected areas (APAs) has been promoted as a means of offsetting the negative consequences that are associated with fishing mortality by protecting the full suite of phenotypes. However, little work has investigated whetherAPAs are able to maintain heterogeneity in behavioral traits in wild fish. We attempted to address this question by using wild BluegillLepomis macrochirusfrom Lake Opinicon, a freshwater system consisting of both anAPAand heavily fished areas. The Bluegill were obtained via angling from three zones in the lake: the main lake area (i.e., fished), theAPA(which has been in place since the 1940s), and a transitional zone between these two areas. In the laboratory, the Bluegill were subjected to two behavioral assessments, a Z‐maze and a flight‐initiation‐distance (FID) test, to address differences in boldness and risk‐taking between these populations. No significant effects of capture zone were detected for any of the behavioral metrics that were assessed in the maze trial. However, individuals that originated from the main lake population had significantly higherFIDscores than the fish from the transitional zone and theAPAdid, indicating that they were more timid. Our results suggest that fisheries activities may only be acting only on specific traits, which may explain some of the null results that are presented here. Nevertheless, our study provides evidence thatAPAs are providing a reservoir of less timid individuals, which is consistent with an evolutionarily enlightened management strategy.
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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".