Ship Biofouling as a Vector for Non-indigenous Aquatic Species to Canadian Arctic Coastal Ecosystems: A Survey and Modeling-Based Assessment
Notice bibliographique
Résumé
Ship biofouling is a major vector for the introduction and spread of harmful marine species globally; however, its importance in Arctic coastal ecosystems is understudied. The objective of this study was to provide insight regarding the extent of biofouling (i.e., percent cover, abundance, and species richness) on commercial ships operating in the Canadian Arctic. A questionnaire was used to collect information on travel history, antifouling practices, and self-reported estimates of biofouling extent from ships operating in the region during 2015–2016. Twenty-five percent of ships operating in the region during the study period completed the questionnaire ( n = 50). Regression trees were developed to infer the percent cover of biofouling, total abundance of fouling invertebrates, and fouling species richness on respondent ships based on previous underwater wetted surface assessments of commercial ships in Canada. Age of antifouling coating system was the only significant predictor of percent cover and total abundance of biofouling invertebrates, while the number of biogeographic realms previously visited and port residence time were significant predictors for fouling species richness. Comparison of relevant travel history features reported through the questionnaire to the regression tree models revealed that 41.9% of 43 respondent ships had antifouling coating systems older than 630 days and are therefore inferred to have relatively high (> 9.3%) biofouling percent cover. More than half of respondent ships (62.8%) had antifouling coating systems older than 354 days and are therefore inferred to have a relatively high total abundance (over 6,500 individuals) of fouling invertebrates. Nearly half of respondent ships (45.9% of 37 ships) had visited at least three biogeographic realms during their last 10 ports-of-call and are therefore inferred to have relatively high fouling species richness (mean 42 taxa). Self-reported estimates of biofouling cover were unreliable, being much lower than model inferences. Although the regression tree models have relatively low predictive power, explaining only 15–33% of the variance in biofouling extent, this study indicates that commercial ships are an active pathway for the transportation of non-indigenous aquatic species to Canadian Arctic coastal ecosystems via biofouling.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».