Use of Rehabilitation Experiments to Understand the Recovery Dynamics of Acid-stressed Fish Populations
Bibliographic record
Abstract
We used rehabilitation experiments involving the stocking of 2 native sportfish, lake trout (Salvelinus namaycush) and smallmouth bass (Micropterus dolomieu), in combination with recent fish community surveys, to study the recovery dynamics of fish populations in acid-stressed lakes near Sudbury and Killarney, Ontario, Canada. Population recovery rates differed between the 2 species. Introduced lake trout did poorly in species-rich lakes and exhibited slower growth, lower survival and delayed recruitment. Smallmouth bass, in contrast, readily colonized species-rich lakes. The biomass of natural smallmouth bass recruits increased to reference lake levels within 5 years following water quality recovery and spawning by stocked fish, whereas the biomass of natural lake trout recruits remained well below reference levels 5-15 years after water quality recovery and spawning by adults occurred. We document introductions by anglers of smallmouth bass into acid-damaged lake trout lakes, including some lakes that did not contain bass prior to acidification. This range expansion of a warm-water species (bass) that can alter food-web structure and reduce the growth of a cold-water species (trout), illustrates the potential for the combination of climate warming and species introductions to greatly alter the biological recovery endpoints in acid-stressed lakes.
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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 | 0.001 | 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".