Benthic algae as bioindicators of agricultural pollution in the streams and rivers of southern Québec (Canada)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The objective of this study was to evaluate the effect of agricultural pollution on periphyton in streams and rivers of southern Québec. We sampled benthic algae incubated from mid-July to mid-August on artificial substrates at 29 sites and analysed the variations in community structure and total community biomass. Diatom community structure as well as total benthic algae community were analysed. Water samples were taken to provide background chemical information, and land use data were also obtained. Preliminary tests showed that colonisation of the artificial substrates (unglazed ceramic tiles) resulted in biomass levels (Chlorophyll a and ash-free dry weight) and species composition that were not statistically different from those on natural rock substrates. The canonical correspondence analyses showed that pH, conductivity and suspended solids were the most significant environmental variables accounting for variations among sites and diatom community structure. No additional resolving power was obtained by including cyanobacteria, green algae and flagellates. This total community analysis substantially increased variance and sample processing time while reducing the relationship with environmental variables. These results indicate that an analysis based exclusively on diatoms provided the optimal approach. Traditional nutrient measurements (phosphorus and nitrogen) did not explain a significant part of the variance in the species composition among sites. The ordination analyses clearly separated agriculturally-impacted streams from reference sites, but no significant grouping was observed related to the intensity and type of agriculture, indicating the greater importance of local farming practices. The use of periphyton as a bioindicator provides an integrated measurement of water quality as experienced by the aquatic biota, and therefore offers a useful addition to physico-chemical water quality monitoring strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 it