Ecological risk assessment of predicted marine invasions in the Canadian Arctic
Bibliographic record
Abstract
Climate change is impacting environmental conditions, especially with respect to temperature and ice cover in high latitude regions. Predictive models and risk assessment are key tools for understanding potential changes associated with such impacts on coastal regions. In this study relative ecological risk assessment was done for future potential introductions of three species in the Canadian Arctic: periwinkle Littorina littorea, soft shell clam Mya arenaria and red king crab Paralithodes camtschaticus. These species occur in locations connected to Canadian Arctic ports through shipping and have the potential to be introduced via ballast water discharge. The methodology proposed in this study is unique in the sense that it considers not only ballast water origin, but also the distribution of the species being assessed and the sensitivity of the receiving habitat. It combines detailed information (ballast water source of each tank, transit time, time of the year when the water is released, environmental suitability of receiving habitat, impact, and habitat sensitivity) in order to assess ecological risk. Through the use of this approach it is highlighted that domestic discharge events pose a higher relative overall risk on a vessel-specific and cumulative annual bases than international discharges. The main ports of Deception Bay and Churchill were classified as being at moderate to high relative risk for L. littorea and M. arenaria, especially from domestic vessels, while relative overall risk for P. camtschaticus was low for international vessels and null for domestic vessels due to few ships transiting from its range of distribution to Canadian Arctic ports. This work can serve as an approach to help build a list of potential high risk species-a "grey" watch list-for the Canadian Arctic, and provides useful information for consideration in future decision making actions such as the identification of high risk pathways, species and ports.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".