The influence of simulated immigration and chemical persistence on recovery of macroinvertebrates from cypermethrin and 3,4‐dichloroaniline exposure in aquatic microcosms
Bibliographic record
Abstract
BACKGROUND: Chemical dissipation and organism immigration are considered important factors that influence recovery potential from perturbation of aquatic macroinvertebrates. Experiments were conducted to investigate the effect of simulated immigration on recovery of aquatic macroinvertebrates exposed in outdoor microcosms to ecotoxicologically similar concentrations of the rapidly dissipating pyrethroid insecticide cypermethrin (70 ng L(-1)) or the more persistent herbicide intermediate and degradate 3,4-dichloroaniline (10 mg L(-1)). Microcosms were covered with light-permeable mesh to prevent recolonisation. Immigration was simulated by the regular addition of organisms after treatment. RESULTS: Microcosms exposed to 3,4-dichloroaniline treatment suffered substantial loss of taxon richness and by 10 months after treatment had only recovered where invertebrates had been added. Those treated with cypermethrin underwent an initial decline in certain crustacean and insect populations. These populations showed some signs of recovery over a period of 5 months through internal processes alone. However, rate of recovery was further enhanced where immigration was simulated, and in this case recovery had occurred around 100 days after treatment. CONCLUSION: Although not the only factors involved, simulated immigration and chemical fate clearly influence the ability of communities to recover from chemical exposure. Consideration of immigration processes and development of models will help to increase the realism of risk assessments.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".