Modeling Management Scenarios and the Effects of an Introduced Apex Predator on a Coastal Riverine Fish Community
Bibliographic record
Abstract
Abstract The flathead catfishPylodictis olivaris, a carnivorous fish species native to most of the central interior basin of North America, has been introduced into at least 13 U.S. states and 1 Canadian province. Concurrent declines in abundance of native fishes have been reported in aquatic systems where flathead catfish have been introduced. To evaluate the potential impact of this invasive species on the native fish community we developed an ecosystem simulation model (including flathead catfish) based on empirical data collected from a North Carolina coastal river. The model results suggest that flathead catfish suppress native fish community biomass by 5–50% through both predatory and competitive interactions. However, our model suggests these reductions could be mitigated through sustained exploitation of flathead catfish by recreational or commercial fishers at rates equivalent to those for native flathead catfish populations (annual exploitation = 6–25%). These findings demonstrate the potential for using directed harvest of an invasive species to assist in restoring native communities.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".