Development of Environmental Thresholds for Nitrogen and Phosphorus in Streams
Bibliographic record
Abstract
Inputs of nutrients (P and N) to freshwaters can cause excessive aquatic plant growth, depletion of oxygen, and deleterious changes in diversity of aquatic fauna. As part of a "National Agri-Environmental Standards Initiative," the Government of Canada committed to developing environmental thresholds for nutrients to protect ecological condition of agricultural streams. Analysis of data from >200 long-term monitoring stations across Canada and detailed ecological study at ~70 sites showed that agricultural land cover was associated with increased nutrient concentrations in streams and this, in turn, was associated with increased sestonic and benthic algal abundance, loss of sensitive benthic macroinvertebrate taxa, and an increase in benthic diatom taxa indicative of eutrophication. Chemical thresholds for N and P were defined by applying five approaches, employing either a predetermined percentile to a water chemistry data set or a relationship between water chemistry and land cover, to identify boundaries between minimally disturbed and impaired conditions. Comparison of these chemical thresholds with biological thresholds (derived from stressor-response relationships) produced an approach for rationalizing these two types of thresholds and deriving nutrient criteria. The resulting criteria were 0.01 to 0.03 mg L(-1) total P and 0.87-1.2 mg L(-1) total N for the Atlantic Maritime, 0.02 mg L(-1) total P and 0.21 mg L(-1) total N for the Montane Cordillera, ~0.03 mg L(-1) total P and ~1.1 mg L(-1) total N for the Mixedwood Plains, and ~0.10 mg L(-1) total P and 0.39-0.98 mg L(-1) total N for the interior prairies of Canada. Adoption of these criteria should result in greater likelihood of good ecological condition with respect to benthic algal abundance, diatom composition, and macroinvertebrate composition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".