MétaCan
Menu
← Back to cohort
Record W7133274142

Vessel biofouling as a vector for nonindigenous species introductions in Canada

2022· other· en· W7133274142 on OpenAlexaffabout
Tessa Rose Brinklow, Farrah T. Chan, Mohammad Etemad, Jiban Chandra Deb, Sarah A. Bailey

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsGovernment of CanadaFisheries and Oceans Canada
Fundersnot available
KeywordsBiofoulingPopulationBallastPropagule pressureInvasive speciesIntroduced speciesInvertebrateFishingArctic
DOInot available

Abstract

fetched live from OpenAlex

Biofouling is the accumulation of organisms (such as algae, mussels, barnacles, and other taxa) on underwater surfaces. Biofouling on vessels is seen as undesirable, as it reduces vessel fuel efficiency through increased drag, and has potential to transfer organisms over long distances to locations outside their natural biogeographic region. Compared to other vectors that transfer aquatic organisms, such as ballast water, biofouling is relatively understudied despite being a major contributing vector of aquatic nonindigenous species (NIS) to coastal ecosystems globally. As a result, Transport Canada requested science advice from Fisheries and Oceans Canada, seeking an updated national assessment of the probability of NIS introduction and establishment via biofouling on vessels, to inform the development of biofouling management policies. This study used a multistage mechanistic model (a multiple-step model describing the parts or stages of the invasion process) to assess the probability of introduction and establishment of NIS into Canada based on one year of data on first arrivals of foreign-flagged commercial vessels. The stages in the model included arrival, survival, and establishment of NIS, but throughout this document the term ‘establishment’ denotes the cumulative success through all three stages to result in a self-sustaining population in Canadian waters. Separate assessments were conducted for vessels’ main hull surfaces and combined niche areas (such as the sea chest, propeller, and thruster tunnels, where biofouling may be more concentrated). Results were summarized for the four coastal regions of Canada based on the destination/arrival port of the vessels: Atlantic, Pacific, Great Lakes-St. Lawrence River, and Arctic regions. The model parameters were based on empirical vessel biofouling and environmental data, as well as estimates of biological processes with variability introduced. Estimates of mean NIS primary establishments per year via vessel hulls ranged from <1 (Arctic region) to 2.2 (Pacific region). Similarly, the mean number of trips until at least one NIS establishment is successful via the hull ranged from 94 (Pacific region) to 174 (Great Lakes-St. Lawrence River region). Primary NIS establishments via vessel niche areas were generally higher than those associated with the hull, with the highest species establishments per year being 8.4, with 23 trips until establishment occurs (Pacific region). While there is uncertainty associated with these estimates, these results indicate a meaningful probability of NIS establishments by vessel biofouling in all regions of Canada. The Atlantic and Pacific coasts are expected to receive the greatest numbers of NIS establishments, driven by the higher number of vessel arrivals to these regions. NIS establishment rates via the main hull areas of vessels were lower compared to niche areas, with the niche areas (all combined) having higher abundance of biofouling but smaller wetted surface area. Vessel biofouling should be considered as a dominant, active vector for introduction of NIS to Canada.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.230
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada→French-language works237,207→