The alarming state of freshwater biodiversity in Canada
Bibliographic record
Abstract
Little is known about the current state of freshwater biodiversity in Canada, one of the countries with the greatest amount of surface waters in the world. To address this knowledge gap, we compiled a list of all available assessments of conservation status for freshwater species (over 3000 taxa) and further evaluated the overall status of six distinct taxonomic groups, focusing on organisms reliant on fresh waters (i.e., aquatic plants, invertebrates (with a focus on freshwater mussels), fishes, herpetofauna (reptiles and amphibians), birds, and mammals). Overall, 11.7% of all freshwater species of plants and animals assessed were found to be “at risk” (i.e., listed as “Threatened”, “Endangered”, or “Extirpated”) and 17.9% identified as “Special Concern”. We found that 37.9% of species lacked sufficient data to enable their status to be assessed. Data gaps in Canada’s assessment of its freshwater species were most prevalent in invertebrates (excluding freshwater mussels). Given the alarming state of freshwater biodiversity in Canada, we conclude by providing recommendations that focus on evaluating temporal trends and informing conservation actions.
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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".