Habitat loss and the limits to endangered species recovery
Bibliographic record
Abstract
Abstract Canada is one of the last places on earth with extensive wilderness areas, yet the number of Canadian species threatened with extinction continues to rise every year. Using satellite‐derived land use data, we find that habitat loss explains most of the variation in numbers of endangered species across Canada. Habitat loss within species ranges is, therefore, likely to be the leading factor inhibiting their recovery. We measured habitat loss individually within the known ranges of 243 terrestrial species at risk of extinction across Canada. Recovery potential, as measured by extent of natural habitat within each species’ range, is bimodally distributed, but less than 50% of the range of the majority of Canada's species at risk is natural habitat and there is no detectable habitat remaining for 16 of the 243 species at risk. There were no differences in the recovery potential of species categorized either by threat level (special concern, threatened, or endangered) or taxon. Despite having extensive wilderness areas, Canada has similar rates of endangerment to other countries in the Americas, underlining the effect of severe habitat loss to intensive agriculture that has occurred in Canada's most biologically diverse regions. Improvements to protected areas networks and especially cooperative conservation activities with private landowners will do the most to improve the recovery prospects of species at risk in Canada.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".