Evolutionary isolation of Canadian terrestrial vertebrate species
Bibliographic record
Abstract
Conservation prioritization has become increasingly important as a practical response to ongoing biodiversity loss and limited resources. One tool, evolutionary distinctiveness (ED) is based on a measure of evolutionary isolation and has merit for identifying taxa with few close relatives. Here we present the first ever national-level ED scores for any jurisdiction, applying the measures to all Canadian tetrapods. We updated and pruned global dated phylogenies of all terrestrial vertebrates (amphibians, squamates, turtles, mammals, and birds) down to native Canadian species and calculated Canadian ED scores and rankings for each and compared them to their global ED ranks. Canada’s terrestrial ectotherm vertebrates (amphibians and reptiles) include most of Canada’s most evolutionarily isolated species and many score and rank higher nationally than globally in their ED scores. These taxa are also the most imperilled in Canada and so species with populations assessed as at-risk by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) represent, on average, more than expected national evolutionary history. Interestingly, several exotic species also have very high national ED scores. To the extent that evolutionary isolation captures aspects of local and national biodiversity worth preserving, our lists may provide useful input to conservation agencies engaging in conservation prioritization exercises.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".