Vessel biofouling as a vector for nonindigenous species introductions in Canada
Bibliographic record
Abstract
Vessel biofouling is a complex process involving a diverse assemblage of aquatic species, which is recognized as an important global pathway for the introduction of NIS. This advice is based on a first quantitative estimate of establishment rates of aquatic NIS associated with initial vessel arrivals to Canada, predominantly by foreign-flagged cargo vessels, using a year-long dataset representative of a typical year of ship traffic. Domestic transits (not included in this assessment) are likely an important mechanism for both primary and secondary NIS introductions that should be explored in future analyses. The probability of NIS establishment by vessel biofouling is considerable. At current rates of shipping, Canada can expect, on average, eight new NIS establishments from biofouling per year in each of the Atlantic and Pacific regions, five in the Great Lakes-St. Lawrence River (GLSLR) region, and two in the Arctic. The results indicate that the probability of NIS establishment from niche areas is greater than from the main hull, despite being proportionally smaller in area, highlighting the importance of niche areas for establishment of NIS. The probability of NIS establishment was greater for container vessels, bulkers, passenger vessels, and tankers compared to other vessel types (tugs and other special purpose), likely due to the higher frequency of arrivals and greater wetted surface area. The lower probability of NIS establishment in the Arctic is largely driven by the currently low level of vessel traffic, while survival and establishment rates are lower in the freshwater GLSLR since NIS associated with vessel biofouling are predominantly marine taxa. Regional differences in probability of NIS establishment are associated with patterns of vessel traffic and size, with container vessels and tankers dominating in the Atlantic region, while bulkers and container vessels dominate in the Pacific region, and all three vessel types are of relatively equal importance in the GLSLR. Bulkers, followed by passenger vessels, currently dominate vessel traffic in the Arctic. Patterns among regions might also be driven by small sample sizes, though there are likely real differences driven by variation in shipping routes (prior ports-of-call) among the regions that should be more thoroughly explored in any future studies. Based on generalized vessel traffic predictions for the Arctic region only, NIS establishments are expected to increase by more than 50%. Predicted habitat suitability is expected to increase across Canadian coasts for selected NIS, and is expected to be greatest in the Arctic region for more cold-tolerant species. However, as a limited number of species have been evaluated (20-30 species per coast), modelling for additional species is needed. Although future establishment rates for all regions could not be modelled at this time, in the absence of intervention, establishments are expected to increase at all Canadian ports with continued ocean warming. It was not possible to forecast the effect of projected changes in shipping activity and temperature on the probability of NIS establishments by vessel biofouling across Canada during this CSAS process for a number of reasons, including unavailability of detailed vessel traffic projections and gaps in projected environmental data for inland and riverine ports, so effort to develop such data is critical. Suggestions on how to more broadly forecast the future probability of NIS establishments across Canada using available data sources were provided and could be undertaken with additional effort in the near future. Uncertainties in the data and parameters used in the model were identified due to factors such as small sample sizes, poor taxonomic resolution and complexity of the biofouling community dynamics (further described below). Other considerations that could not be addressed here, but warrant future attention, include the influence of different antifouling coatings, vessel duration of stay in ports, cumulative effects of multiple vessel arrivals through time and species-specific variability in survival and establishment (further described below).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".