Use of Diatoms and Macroinvertebrates as Bioindicators of Water Quality in Southern Ontario Rivers
Bibliographic record
Abstract
The effectiveness of diatoms and macroinvertebrates as indicators of environmental conditions in lotic systems was compared in a regional assessment. Benthic samples were collected during summer 2000 from 35 Provincial Water Quality Monitoring river stations in the Grand, Credit, Maitland and Upper Thames watersheds in southern Ontario. Patterns of diatom and macroinvertebrate taxon distributions in relation to environmental variables were determined using canonical correspondence analysis (CCA). Total nitrate, phosphate, conductivity and alkalinity were significant in explaining diatom data, while alkalinity, total nitrate, ammonium and total Kjeldahl nitrogen were significant in explaining invertebrate data. The eigenvalues of the first two CCA axes were significant (p < 0.05) for both diatoms and invertebrates, while the invertebrate analysis explained more taxonomic variation (19% vs. 12%). Regression and calibration models were developed for total nitrate. The correlation between taxon-inferred and observed values was higher for diatoms than invertebrates in the analysis (0.70 vs. 0.59), however, cross-validation with bootstrapping indicated that apparent coefficients may be inflated. Biotic indices were also calculated. The composite invertebrate metric scores gave a slightly closer representation of water quality conditions than the diatom trophic index, but, biotic indices were not as effective as CCA in describing sites. Overall, the invertebrate and diatom communities were similar in their abilities to predict water quality.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".