Stable isotope analysis provides novel insights for measuring lake ecosystem recovery following acidification
Bibliographic record
Abstract
Unstable and simplified freshwater food webs impair the resilience of Canadian fisheries facing environmental stressors. This study utilizes stable isotope analyses to assess trophic recovery to explore food web resiliency in lakes historically impacted by metal mining in Sudbury, Ontario. Carbon (δ13C) and nitrogen (δ15N) stable isotope ratios were quantified in yellow perch ( Perca flavescens), smallmouth bass ( Micropterus dolomieu), and baseline organisms to develop quantitative population metrics and describe dietary niche partitioning. The most severely damaged lake with a barren watershed had the lowest trophic positioning, smallest body size and niche area, and greatest niche overlap among fish species. Semi-barren and forested watershed lakes were more similar to reference lakes in isotopic metrics; however, elevated niche overlap and reduced trophic positioning suggests recovery in these lakes is ongoing. We found that including stable isotope analyses in lake recovery studies provided critical insights not captured by traditional biomonitoring approaches.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".