Vessel biofouling as a vector for nonindigenous species introductions in Canada
Notice bibliographique
Résumé
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).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».