Effects of an experimental rainbow trout (Oncorhynchus mykiss) farm on invertebrate community compositionThis paper is part of the series “Forty Years of Aquatic Research at the Experimental Lakes Area”.
Bibliographic record
Abstract
We examined the development of changes in the zoobenthos along a transect from an experimental rainbow trout ( Oncorhynchus mykiss ) farm in Lake 375, Experimental Lakes Area, northwestern Ontario, Canada. After 2 months, invertebrate abundance was reduced under the fish cage (2542 ± 569 individuals·m–2) compared with samples collected 45 m away (16 137 ± 2624 individuals·m–2). Taxa richness was also depressed, but changes in biomass were variable. Reductions in abundance and richness at high organic loading levels are consistent with earlier models developed for the marine environment of responses to organic loading in marine systems. After two production cycles, the significant principal components axis explaining 76% of total variance in abundance was correlated with distance from the cage (Spearman rank correlation, r = –0.775, p = 0.014) and with chemical variables recommended for freshwater aquaculture monitoring (Pearson’s correlation coefficient, r = 0.78, 0.76, and 0.75 with p = 0.013, 0.018, and 0.020 for pore-water ammonia and sediment Cu and Zn, respectively). The effects of farming were localized, dissipating within 15 m of the cage edge. Invertebrate abundance demonstrated the most potential for incorporation into monitoring schemes at new farms. At established farms, richness may be a valuable monitoring metric.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".