MétaCan
Menu
← Retour à la cohorte
Enregistrement W6929753715 · doi:10.5281/zenodo.10730768

Plant health status of Fagus spp.(FAGUSTAT)

2024· report· en· W6929753715 sur OpenAlexaboutno aff

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2024
Typereport
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBeechFagus sylvaticaTwigFagaceaeDiseaseTransmission (telecommunications)

Résumé

récupéré en direct d'OpenAlex

Beech Leaf Disease (BLD) was detected in Ohio, USA, in 2012, on American beech (F. grandifolia). Since then it has spread to 12 northeastern states and Canada (Ontario), in forests and landscaped areas. The symptoms of BLD include interveinal dark bands on the leaves, crinkling and irregularly thickened leaves and twig dieback; ultimately leading to decline and death of young trees within years. Beech Leaf Disease causes severe damage to stands of F. grandifolia, but also to European beech, F. sylvatica, the main beech species in Europe. A new nematode, Litylenchus crenatae subsp. mccannii (Carta et al., 2020), is now considered as the causal agent of BLD (Vieira et al., 2023) but it was suggested that other microorganisms also play a role in the disease (Burke et al., 2020; Ewing et al., 2021). Pathways of transmission between trees have not been elucidated yet; they might include windborne water, mites, insects, or birds. BLD has never been reported from Europe and could be a severe threat to Fagus spp. stands. In this project, we made a first assessment of the presence/absence of BLD in Europe. Surveys were organised in Belgium, Ireland, the Netherlands, Romania, Slovenia and the UK. A fact sheet about BLD was made to inform people in the field and samples were collected using a common sampling strategy. Samples were taken during summer and fall (July-November) in 2021 and 2022, from beech trees showing symptoms similar to those caused by BLD. This resulted in 658 samples taken at 561 sites. More sites were visually inspected, but not all had trees showing BLD-like symptoms. Nematodes were extracted from leaves, buds and beechnuts, using the Baermann technique, with or without mistifier. Occasionally some non-plant parasitic nematodes were observed, but Litylenchus crenatae subsp. mccannii was never found. This project also aimed to increase public awareness of BLD and encourage the reporting of symptoms. Therefore, people in the field (inspectors, foresters, botanic gardens, parks, arboreta, NPPO…), as well as the general public, were informed via leaflets, posters, presentations, newsletters, publications in specialized magazines, institutional websites or observation platforms. Although the nematode was not found, the microbiome of symptomatic and healthy leaves was studied in Belgium and UK, using RNA-sequencing (metatranscriptomics) and metabarcoding. There were no clear differences compared with genera of bacteria and fungi reported from America. The drivers for the fungal and bacterial leaf microbiome, studied using barcoding, were mainly “location” and “environment” (nursery vs forest). Attempts were made to obtain inoculum of L. crenatae for the evaluation of the host status of European beech cultivars and to study the nematode’s behaviour under European climatic conditions (in confined conditions), but acquiring the nematode was very difficult. Moreover, attempts to culture the nematode on carrot disks, fungal mycelium, in beech plantlets and on beech callus failed. We engaged with BLD researchers in the USA and Canada through regular online meetings with BLD researchers, receiving valuable and updated information. To assess the possibilities of entry from America or Asia, information was gathered on the origin of beech tree materials. As current legislation does not allow import, except for some cases which require phytosanitary certificates, entry of infected leaves is theoretically impossible. Imports with BLD, could have occurred some decades ago however, so vigilance for the presence of BLD is still appropriate. The obtained information will contribute to pest risk assessments for Europe and the development of appropriate measures for protecting Fagus spp. in Europe.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,016

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,085
Tête enseignante GPT0,317
Écart entre enseignants0,233 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2024
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueZenodo (CERN European Organization for Nuclear Research)→Travaux en français237 207→