The state of Canada’s biosecurity efforts to protect biodiversity from species invasions
Bibliographic record
Abstract
Invasive alien species (IAS) pose threats to native biodiversity globally and are linked to numerous negative biodiversity impacts throughout Canada. Considering the Canadian federal government’s commitments to environmental stewardship (e.g., the Convention on Biological Diversity), the successful management of IAS requires an understanding of how federal infrastructure, strategies, and decisions have contributed to previous outcomes. Here, we present an analysis of current efforts by the federal government to prevent IAS establishment in Canadian ecosystems and the unique challenges associated with Canadian IAS management. We then examine historical and current case studies of IAS in Canada with variable outcomes. By drawing comparisons with IAS management in the United States, Australia, and New Zealand, we discuss how the Canadian government may refine its policies and practices to enable more effective responses to IAS threats. We conclude by considering how future interacting stressors (e.g., climate change) will shape how we address IAS threats, and list six lessons for successful management. Most importantly, Canada must regard biodiversity impacts from IAS with as much urgency as direct economic impacts that have historically garnered more attention. Although we focus on Canada, our findings may also be useful in other jurisdictions facing similar challenges with IAS management.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".