AREP CONUS-CA-HI: Annotated Registry of Established Forest Pathogens
Notice bibliographique
Résumé
General understanding of emergent diseases in forest systems, as well as the ability to assess risk of future introductions within a process-barrier framework of biological invasion, are impeded by a lack of systematically compiled information on origins and functional traits of pathogens that have become established outside their range. To address these gaps, substantially update previous registries, and provide critical biosecurity information, from 2021 to 2024 we assembled a list of established forest phytopathogens that are present, but not thought to be native in the continental United States (CONUS), Canada (CA), and the Hawaiian islands (HI) under working hypotheses of their origins. We restricted the present list to phytopathogens that cause disease on native tree or woody shrub species, excluding the larger number of species of non-native phytopathogens of trees that are exclusive to agricultural and horticultural species and landscapes which are already well-represented in pest databases (e.g., CABI, EPPO, APHIS, etc.). We used previous databases as a scaffold and supplemented those lists with additional taxa by cross-referencing with lists of forest pathogens and hypothetical origins for other regions (Australia and Europe) as well as by reviewing taxonomic, host, and distribution history of pathogen species that have been recorded in both the study area (CONUS-CA-HI) and at least one other continent. For each of the 93 species in our database, we provide a relational database of a) taxonomic information, b) invasion status in each region, c) first year on record in each region, d) working hypotheses of original range (where possible), e) traits including disease type and name, dispersal mode, and organs and host life stages infected, f) major hosts, g) and > 7,000 chronological records of potential location-year and host-location-year combinations for each pathogen. We also provide a reference-annotated classification system for types of evidence for first years (c), original ranges (d), and major hosts (f). A draft version of this database was reviewed by forest health experts via targeted online surveys and at a workshop of forest pathologists in January 2024 and by the Forest Pathology Committee ahead of the 2025 national meeting of the American Phytopathological Society in Hawaii. This represents a significant expansion compared to previous registries of non-native infectious microorganisms of forest trees in terms of its comprehensiveness, precision, and accuracy of information that includes a way to assess and compare the level of uncertainty associated with key information.
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 | 0,000 | 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 | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».