SPATIAL, SEASONAL AND INTER‐ANNUAL VARIABILITY IN ENVIRONMENTAL CHARACTERISTICS AND PHYTOPLANKTON STANDING STOCK OF THE TEMPERATE, LOWLAND RIDEAU RIVER, ONTARIO, CANADA
Bibliographic record
Abstract
ABSTRACT Chlorophyll‐ a , biomass and living unit concentrations were monitored across the Rideau River over a three‐year period. The results show that a continuum of changing physical, biological and chemical conditions altered the phytoplankton standing stock of the Rideau River. From year to year, weather conditions and anthropogenic impacts like discharge control had a clear effect on the phytoplankton community. The year 2000, with poorer growing conditions and higher flow regime, had a significantly lower phytoplankton standing stock across all the stations. Based on hydrological characteristics, the Rideau River was divided into four distinct reaches, and ANOVAs show a clear reach effect on phytoplankton standing stock. The invasive zebra mussel consistently reduced the phytoplankton standing stock downstream from the main invasion zone over the three years, although there were differences between years. The non‐native zebra mussel further altered the phosphorus–phytoplankton standing stock relationship. Nutrients, ions and metals were not clearly correlated to standing stock in this three‐year study, although the significant effect of the four reaches suggested that environmental characteristics other than hydrological conditions may have an influence. Phytoplankton development downstream followed a polynomial model. However, unlike the stages of development characterizing many river continuum models, the pattern observed in the present study was affected by zebra mussels followed by anthropogenic impacts of discharge control and eutrophication. This and other studies on the Rideau River highlight the significance of scale (spatial and temporal) and metrics selected when evaluating environmental impacts and developing watershed models. Copyright © 2011 John Wiley & Sons, Ltd.
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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) | 0.001 | 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 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".