Response of non-native lake trout (<i>Salvelinus namaycush</i>) to 15 years of harvest in Yellowstone Lake, Yellowstone National Park
Bibliographic record
Abstract
Introduced lake trout ( Salvelinus namaycush ) threaten to extirpate native Yellowstone cutthroat trout ( Oncorhynchus clarkii bouvieri ) in the 34 000 ha Yellowstone Lake in Yellowstone National Park, USA. Suppression (and eventual eradication) of the lake trout population is deemed necessary for the conservation of Yellowstone cutthroat trout. A US National Park Service gill-netting program removed nearly 450 000 lake trout from Yellowstone Lake from 1995 through 2009. We examined temporal variation in individual growth, body condition, length and age at maturity, fecundity, mortality, and population models to assess the efficacy of the lake trout suppression program. Population metrics did not indicate overharvest despite more than a decade of fish removal. The current rate of population growth is positive; however, it is lower than it would be in the absence of lake trout suppression. Fishing effort needs to increase above observed levels to reduce population growth rate below replacement. Additionally, high sensitivity of population growth rate to reproductive vital rates indicates that increasing fishing mortality for sexually mature lake trout may increase the effectiveness of suppression. Lake trout suppression in Yellowstone Lake illustrates the complexities of trying to remove an apex predator to restore a relatively large remote lentic ecosystem with a simple fish assemblage.
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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 | 0.001 |
| 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".