An analysis of threats and factors that predict trends in Canadian vertebrates designated as at-risk
Bibliographic record
Abstract
The identification of factors that predict trends in population abundance is critical to formulate successful conservation strategies. Here, we explore population trends of Canadian vertebrates assessed as “at-risk” by the Committee on the Status of Endangered Wildlife in Canada and the threats affecting these trends using data from the Canadian Living Planet Index. We investigate how threat profiles—the combination of threats for a given species—vary among species and taxonomic groups. We then investigate threat profile as a predictor of temporal trends—both exclusively and in combination with additional biotic and abiotic factors. Species had 5.06 (±2.77) threats listed on average, and biological resource use (BRU) was the most frequently cited. Our analysis also revealed an association between taxonomic group and population trends, as measured by the proportion of annual increases (years with a positive interannual change). By contrast, the predictive power of threat profile was poor. This analysis yielded some useful insight for conservation action, particularly the prioritization of abating BRU. However, the predictive models were not as meaningful as originally anticipated. We provide recommendations on methodological improvements to advance the understanding of factors that predict trends in population abundance for prioritizing conservation action.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".