Indirect effects of metal-contamination on energetics of yellow perch (Perca flavescens) in Sudbury area lakes, resulting from food web simplification
Bibliographic record
Abstract
Metal-contamination of lakes simplifies food webs and reduces the efficiency of energy transfer to top trophic organisms, such as yellow perch (Perca flavescens). Benthic invertebrate community composition and yellow perch diet, growth and activity levels from lakes along a metal-contamination gradient were used to assess the importance of a naturally diverse prey base for maintaining energy transfer to growing fish, and how this is disrupted by metal-contamination. As perch grow larger, they shift their diet to larger prey; otherwise, the activity costs of foraging for many, small prey, instead of a few large prey, become too high and the fish stop growing. Metal contaminated lakes have less diverse zoobenthic communities, particularly the lack of large bodied invertebrate taxa, forcing perch to rely on smaller benthic prey. Perch from metal-contaminated lakes display slow growth and poor condition during benthivory. Estimates of fish activity, using the activity of the glycolytic enzyme Lactate dehydrogenase in perch white muscle tissue as a proxy, suggest that diet shifts to larger prey lower activity costs and may explain how diet shifts maintain growth efficiency as perch grow larger. Perch from metal-contaminated lakes cannot benefit from the energetic advantages of switching to larger prey and thus exhibit poor growth.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".