MétaCan
Menu
← Retour à la cohorte
Enregistrement W2898706657 · doi:10.1242/jeb.170274

Enemy at the bat cave door

2018· article· en· W2898706657 sur OpenAlexaffabout
Oana Birceanu

Notice bibliographique

RevueJournal of Experimental Biology · 2018
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueBat Biology and Ecology Studies
Établissements canadiensWilfrid Laurier University
Organismes subventionnairesnon disponible
Mots-clésThreatened speciesBiological dispersalBiologyEcologyFungusDozenBeakZoologyBotanyPopulation

Résumé

récupéré en direct d'OpenAlex

TV shows such as ‘Dracula’ and the ‘Batman’ series have made bats famous over the years. We all know that they are the only mammals adapted for flight, but did you know that some plants depend solely on bats for pollination and seed dispersal; or that they consume so many insect pests in a few hours that they reduce the need for insecticides? Bats are true engineers of their environment, but the populations in North America are currently threatened by an outside enemy: the European fungus, Pseudogymnoascus destructans, which causes white nose syndrome, leading to death. How the fungus spreads and adapts to new environmental challenges (e.g. colder or warmer climate) has not been studied extensively.With this in mind, Adrian Forsythe, a PhD student at McMaster University in Hamilton, Canada, along with a team of colleagues from the same institution, have investigated how well the white-nose syndrome fungus adapts to varying temperatures, and how far and how fast it can spread in new regions that are warmer or cooler. Over the course of 5 years (2008–2013), the team collected samples of the fungus from bats in different locations across North America. Analysing the fungus colony samples, the authors were able to establish that they all varied in terms of colony size, colour and how the pigment was distributed. The group examined colony size because it is an indicator of the ability of the fungus to obtain nutrients from the environment and reproduce, but they also looked at pigmentation as an indicator of resistance to environmental challenges and the ability of the fungus to spread rapidly.Comparing the new samples with the very first sample that was collected when the infection was initially identified in North America, 10 years ago in New York State, it was clear that the fungus had changed (or had adapted) to each specific location. The authors found that the colony size and pigmentation varied significantly the further the sample was from the original infection site, meaning that the fungus was adapting to its new environment; it was coping well with new environmental challenges and it was spreading at an alarming rate. To further test the resilience of the fungus, the research team picked four samples representing the differences in colony size and pigmentation within all groups and exposed them to 4°C, 13°C and 23°C for varying lengths of time, after which they looked at growth and genetic differences in the fungi. The team found that different strains of white-nose syndrome fungus from different locations preferred different temperatures and grew at different rates, but the most interesting finding was the presence of genetic mutations among the fungal groups, suggesting that it is adapting rapidly to its environment.Bats are crucial for the health of ecosystems, from hunting harmful insects, such as mosquitos, to plant pollination and providing fertilizer for agriculture; a world without bats would be catastrophic. Through their work, Forsythe and his team have provided additional information on the spread of white-nose syndrome fungus and on the factors that influence and contribute to its rapid adaptation to the North American climate, but more research is needed to better understand and prevent its spread, which seems to have North American bats cornered.

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)0,001
score de la tête « metaresearch » (Gemma)0,002
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,278
Score d'incertitude au seuil0,930

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0080,002
Communication savante0,0040,004
Science ouverte0,0010,005
Intégrité de la recherche0,0030,005
Charge utile insuffisante (le modèle a refusé de juger)0,2780,082

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 Opus0,026
Tête enseignante GPT0,276
Écart entre enseignants0,250 · 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
GenreEmpirique

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

En bref

Citations0
Publié2018
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueJournal of Experimental Biology→Même sujetBat Biology and Ecology Studies→Travaux en français237 207→