Influence of runoff regime type on a macroinvertebrate‐based flow index in rivers of British Columbia (Canada)
Bibliographic record
Abstract
ABSTRACT Anthropogenic pressure on flow regimes has been recognized as a significant threat to the health of rivers in Canada and elsewhere. Yet while we know that the historical hydrological conditions prevailing at river sites can be assigned to runoff regime types, the implications of this hydrological structure on biological community composition have been poorly studied. Here we support the improvement of guidelines for flow management by exploring the relationship between biota and runoff regime types for selected rivers in British Columbia. One thousand six hundred biological samples were extracted from Environment Canada's Canadian Aquatic Biomonitoring Network (CABIN) database and a matching procedure was undertaken to associate biological samples to the long‐term hydrometric monitoring stations stored in the HYDAT National Water Data Archive. A practical approach for spatial matching of hydrometric and biomonitoring sites was presented, which permitted matching of a sufficient number of samples to assess the structure of biological communities across the four regime types identified. By examining multivariate and univariate biological descriptors, including the recently developed Canadian Ecological Flow Index, differences in macroinvertebrate community composition between the runoff regimes were observed. In conclusion, we have developed a practical approach to match hydrological and biomonitoring data and we have forwarded guidelines on how to improve integration between hydrometric and biomonitoring networks. Moreover, we have provided the first ecological validation of runoff regime types in Canada, confirming the need to account for antecedent hydrological conditions in the assessment of ecological quality using biomonitoring data. Copyright © 2011 John Wiley & Sons, Ltd. and Crown in the right of Canada
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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) | 0.007 | 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".