Effects of organophosphorus insecticide and inorganic nutrients on the planktonic microinvertebrates and algae in a prairie wetland
Bibliographic record
Abstract
Manipulations of the planktonic microinvertebrate community in a prairie wetland were carried out in experimental enclosures in Delta Marsh, Canada. Lorsban 4E (active ingredient chlorpyrifos) was applied once to treatment enclosures at a nominal concentration of 10 μg/L. Additions (thrice weekly) of inorganic nitrogen and phosphorus were made to treatment enclosures for the duration of the 10-week expermental period. One-way ANOVA was used to discern treatment effects on the microinvertebrate community at the group level. Impacts of insecticide or inorganic nutrient addition on major groups of microinvertebrates (Cladocera, Cyclopoida and Calanoida Copepoda, Rotifera) were limited, with few significant density changes observed during the experiment. Canonical correspondence analysis (CCA) was used to analyse the structure of the microinvertebrate community at the species leve. Percent cover of enclosure bottom by submersed macrophytes and alkalinity were the only significant environmental variables: 10 environmental variables in the CCA accounted for 90 % of the variance in the microinvertebrate species data. Differential mortality of arthropod microinvertebrates resulted from chlorpyrifos addition; calanoid copepods were more tolerant than cladocerans and cyclopoid copepods. An increase in the proportional abundance of small planktonic rotifers was observed after insecticide treatment, probably due to decreased competition with cladocerans and reduced cyclopoid copepod predation. Inorganic nutrient addition did not substantially alter the microinvertebrate community structure.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".