A risk assessment for the introduction of invasive fish for Kejimkujik National Park and National Historic Site, Canada
Bibliographic record
Abstract
Recent research has highlighted the need for invasive species risk assessments that consider multiple factors, such as habitat suitability and life history. With invasive species encroaching on the boundary of Kejimkujik National Park and National Historic Site (Kejimkujik), Canada, there is concern surrounding the potential ecological effects on the Park’s freshwater ecosystems. Herein we present a multifactor risk analysis for the risks of introduction of two invasive species, smallmouth bass and chain pickerel. Methods included computer-based analysis of cost–distance and habitat suitability, and a literature-based review of management techniques. Smallmouth bass were found to have a high risk of establishment and consequent ecological effects in Kejimkujik. Although chain pickerel can also negatively affect aquatic communities, their separation from the Park’s primary watershed and low dispersal ability resulted in lower levels of risk. Four recommendations were developed following a review of management techniques: (1) containment of the source population for smallmouth bass; (2) public education, outreach and communication; (3) monitoring and rapid response upon detection; and (4) collaboration with other parties. Although the present study focused on Kejimkujik, similar challenges for invasive freshwater fish assessment and mitigation exist elsewhere, and our methods may prove illustrative for researchers and managers working under similar conditions.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".