Saskatchewan Condition Assessment of Lotic Ecosystems (SCALE): A multivariate tool for assessing the integrity of Northern Great Plains wadeable rivers and streams
Bibliographic record
Abstract
Human access to surface water resources in the Northern Great Plains (NGP) is challenged by availability and quality, and ecosystem health objectives for these characteristics have not been well developed. Here, we present a predictive multivariate model using the reference condition approach to inform goals for ecosystem health assessment. Benthic communities and abiotic variables were collected at 280 potential reference sites and 8 test sites, and of these, reference sites with least amount of human activity (n = 83) were classified into three community groups and summary metrics. Discriminant function analysis and cross-validation determined that stream order and ecoregion predicted 68.7% of the sites correctly, thus enabling comparison of sites with unknown condition to reference site groups. We then evaluated metrics through Test Site Analysis and stressor gradient analysis in each biological group. Beetle and amphipod fauna were found to be important for condition assessment in addition to traditional metrics of species richness, abundance, detritivory, Ephemeroptera/Plecoptera/Trichoptera dominance, and assemblage composition. These results provide least disturbed reference condition and ecological insights into land use impacts in the NGP. Ultimately, this model is an effective tool for evaluating biotic condition, enables prioritizing river management strategies, and can quantify the efficacy of mitigation measures.
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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 | 0.000 |
| 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 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".