Hopeful insights from wildlife recoveries in Canada
Bibliographic record
Abstract
Facing the global biodiversity crisis, conservation practitioners and decision-makers seek to catalyze wildlife recoveries in their region. Here we examined social-ecological attributes related to threatened species recovery in Canada. First, we used a retrospective approach to compare the trajectories of the original species assessed by Canada’s species-at-risk committee and found that only eight of 36 species now have decreased extinction risk relative to the past. There were no significant differences in human or financial capacity provided for recovery across species doing better, the same, or worse; the only significant difference was whether the primary cause of decline was alleviated or not. Second, when looking at species assessed at least twice between 2000 and 2019 we found that only eight of 422 (1.9%) experienced both increasing abundance and decreasing extinction risk. The defining characteristic of successful recoveries was first alleviating the original cause of decline, which was most often accomplished through strong regulatory intervention. Once declines were halted, practical interventions were highly species-specific. It is instructive to learn from conservation successes to scale resources appropriately and our results emphasize the importance of threat-specific intervention as a fundamental precursor to the successful restoration of biodiversity in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".