Food web alterations that promote native species: the recovery of cisco (<i>Coregonus artedi</i>) populations through management of native piscivores
Bibliographic record
Abstract
We evaluated the effects of fisheries management on food webs in three northern Wisconsin lakes with exotic rainbow smelt (Osmerus mordax). In two of the lakes, restrictions on fishing reduced mortality rates on adult walleye (Sander vitreus) during the study period. In these lakes, walleye populations increased concurrently with a decline in rainbow smelt populations. As rainbow smelt populations declined in both lakes, native cisco (Coregonus artedi) populations increased. Our analysis of walleye diets illustrated that walleye fed selectively on rainbow smelt but did not feed on cisco during the summer months. When entered into bioenergetics simulations, this information demonstrates that walleye predation alone was enough to cause the observed rainbow smelt declines in our study lakes. Our results indicate that increased walleye density allows for a parallel increase in cisco density. Based on our results, fishery regulations to restore walleye to high densities in lakes invaded by rainbow smelt may restore native planktivores that have co-evolved traits.
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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 | 0.000 | 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".