Multiple impacts of invasive species on species at risk: a case study in British Columbia, Canada
Bibliographic record
Abstract
Invasive species are a leading cause of biodiversity loss and species extinctions across ecosystems on a global scale. The historical and ongoing focus on single-species management of invasive species and species at risk contributes to inefficiencies in management strategies that present an obstacle to achieving desired outcomes. A holistic approach that consolidates and maps linkages between the broader collective of invasive species and species at risk in an area provides a more appropriate entry point for issue-based, rather than species-based, management planning. We present a case study of this approach from British Columbia, Canada, which synthesized the identity, mechanisms of impact, mechanisms of spread, and magnitude of impacts across 782 unique pairs of invasive species and federally listed species at risk, based on a literature review of species at risk documentation. The resulting dataset was used to summarize the nature of interactions across species pairs and taxonomic groups to help guide the development of invasive species response strategies that make the best use of limited management resources. As species invasions and extinctions become increasingly interconnected, holistic approaches rooted in cumulative effects assessment and ecosystem-based management can provide a stronger foundation for reducing or mitigating this growing threat.
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 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".