A comprehensive assessment of ship-mediated invasion risk in the Canadian Arctic
Bibliographic record
Abstract
Ships' ballast water and hull fouling are leading transport vectors of aquatic nonindigenous species (NIS) globally, yet very few studies have examined the magnitude of these vectors in the Arctic. A combination of climate warming, resource exploration, and expanded Arctic shipping is expected to increase the risk of introducing NIS to the Arctic via ship vectors. Therefore, a formal assessment of the current risk levels associated with these vectors is warranted. I conducted a vector-based risk assessment to identify ports at relatively high risk of ballast-mediated invasions and the responsible vessel pathway. Churchill appears to be at greatest invasion risk from ballast water discharged by international merchant vessels. I subsequently collected ballast water and hull fouling samples from 32 and 13 ships, respectively, at Churchill and quantified colonization pressure (CP) and total propagule pressure (total PP) associated with each vector. I evaluated relative arrival potential of invertebrates via ballast water by comparing CP, total PP, and the relationship between CP and total PP in vessels from Europe destined for the Arctic with those bound for Atlantic Canada and the Great Lakes. Arrival potential of invertebrates in ballast water of Arctic ships may be lower than that of Atlantic ships but similar to that of Great Lakes ones. Furthermore, I determined the relative importance of ballast water and hull fouling as transport vectors of NIS to the Canadian Arctic by comparing CP, total PP, number of NIS, and total abundance of all NIS for invertebrates transported by each vector. Hull fouling appears to be the more important transport vector of NIS. Finally, to better understand ship-mediated dispersal mechanisms, I examined temporal changes in characteristics of species assemblages entrained by ballast water using datasets from other, previously studied Canadian systems with large sample size. Rank-abundance distributions and CP:total PP patterns varied widely by voyage route (Pacific vs. Atlantic), taxonomic group (invertebrates, diatoms, and dinoflagellates), and ballast water management (control vs. exchanged). Results of this dissertation can help direct research and management efforts at high-risk ports as well as the vector and vessel pathways that pose the greater risk given limited managerial resources.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 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".