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Hull fouling as an invasion vector: can simple models explain a complex problem?

2011· article· en· W2122629677 on OpenAlex
Francisco Sylvester, Odion Kalaci, Brian Leung, Anaïs Lacoursière‐Roussel, Cathryn Clarke Murray, Francis Choi, Monica A. Bravo, Thomas W. Therriault, Hugh J. MacIsaac

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Applied Ecology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsFisheries and Oceans CanadaUniversity of British ColumbiaMcGill UniversityBedford Institute of OceanographyUniversity of Windsor
Fundersnot available
KeywordsPropagule pressurePropaguleHarbourHullBallastFoulingInvasive speciesBiofoulingColonizationFisheryEcologyGrazing pressureEnvironmental sciencePort (circuit theory)Introduced speciesGeographyBiologyMarine engineeringEngineeringGrazingComputer scienceDemography

Abstract

fetched live from OpenAlex

Summary 1. The most effective way to manage nonindigenous species and their impacts is to prevent their introduction via vector regulation. While ships’ ballast water is very well studied and this vector is actively managed, hull fouling has received far less attention and regulations are only now being considered despite its importance for introductions to coastal, marine systems. 2. We conducted comprehensive in situ sampling and video recording of hulls of 40 transoceanic vessels to assess propagule and colonization pressure in Vancouver and Halifax, dominant coastal ports in Canada. Concomitant sampling was conducted of harbour fouling communities to compare hull and port communities as part of a vector risk assessment. 3. Although this vector has been operational for a long time, hull and harbour communities were highly divergent, with mean Sørensen’s similarity values of 0·03 in Halifax and 0·01 in Vancouver, suggesting invasion risk is high. Propagule pressure (up to 600 000 ind. ship −1 ) and colonization pressure (up to 156 species ship −1 ) were high and varied significantly between ports, with Vancouver receiving much higher abundances and diversity of potential invaders. The higher risk of fouling introductions in Vancouver is consistent with historical patterns of successful hull fouling invasions. 4. The extent of hull fouling was modelled using ship history predictors. Propagule pressure increased with time spent in previous ports‐of‐call and time since last application of antifouling paint, whereas colonization pressure increased with time since last painting and with the number of regions visited by the ship. Both propagule and colonization pressure were negatively related to the time spent at sea and the latitude of ports visited. 5. Synthesis and applications . A major challenge for applied invasion ecology is the effective management of introduction vectors. We found that hull fouling has a strong potential for introduction of many species to coastal marine habitats and that management should be considered. Simple variables related to the vessels’ hull husbandry, voyage, and sailing patterns may be used to predict and manage hull fouling intensity. The results presented here should interest policy makers and environmental managers who seek to reduce invasion risk, and ship owners seeking to optimize fuel efficiency.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.000

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 head0.049
GPT teacher head0.234
Teacher spread0.186 · 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