Development of a benthic macroinvertebrate flow sensitivity index for Canadian rivers
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Bibliographic record
Abstract
Abstract Widespread alteration of flow regimes requires guidelines for the protection of river ecosystems based on sound science. Preservation of the biodiversity within river ecosystems and sustaining natural ecological functions are key aspects of their management. However, the relationship between the biota and flow‐related phenomena is poorly understood and, as a consequence, over‐simplistic hydrology‐based guidelines for river management have been adopted without establishing clear indicators of success. In the present paper, we aim to support the improvement of guidelines for flow (current velocity) management by developing a flow sensitivity index based on macroinvertebrates for Canadian rivers. Using benthic macroinvertebrate (BMI) samples collected by the Canadian Aquatic Biomonitoring Network (CABIN), current velocity preferences for the 55 most common invertebrate taxa across a range of reference and potential reference sites were derived. A Canadian Ecological Flow Index (CEFI) was developed based on these preferences. By testing the index against independent data, CEFI was found to respond mainly to changes in hydraulic conditions, and was minimally influenced by confounding factors (e.g. stream type, organic enrichment). The index was further validated using two independent data sets from the west and east of Canada, suggesting countrywide applicability of the method. In conclusion, we have developed a practical approach to evaluate relationships between hydrological regime and an important component of the river biota, permitting the development of an index which has good potential as an indicator for the effects of flow alteration. Moreover, we outline how the CEFI could be used as a tool for the development of holistic guidelines for the estimation of riverine flow needs. Copyright © 2010 Crown in the right of Canada and John Wiley & Sons, Ltd.
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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 | 0.001 | 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) | 0.000 | 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