Novel associations among insect herbivores and trees: Patterns of occurrence and damage on pines and eucalypts
Notice bibliographique
Résumé
Globalization has led to a significant increase in the establishment of forest plantations with exotic species and to the accidental introduction of forest insects worldwide. Cumulatively, these factors contribute to the increased occurrence of novel associations between phytophagous insects and trees, leading to new interactions between species that have not historically co-occurred. Here, we reviewed the patterns of novel associations between herbivorous insects and pines and eucalypts at a global scale and identified factors that could favor the occurrence of novel associations and their impacts on forestry. We recorded 766 novel associations of insects with pines and 356 with eucalypts, involving 852 species of herbivorous insects. Most of the novel associations occurred in the Neotropic, Austro-Pacific, and Palearctic regions. In all biogeographic regions, novel associations involved mostly native insects on exotic trees, except for the Nearctic, where exotic insects were dominant. Generalist insects were more frequently involved in novel associations, but specialist ones caused higher damage levels. Foliage feeders and wood and phloem feeders were the most frequent feeding guilds involved in new associations, while sap feeders, shoot feeders, and fruit and seed feeders were rare. For pines, non-native insects were more frequently associated with trees phylogenetically related to hosts in their native range, and native insects were more frequently associated with unrelated hosts. However, for both exotic and native insects, novel associations with eucalypts primarily involved hosts that are unrelated to hosts in their native range. The significance of extensive forest plantations with non-native species and the biogeographic context are emphasized as factors associated with the occurrence of novel associations between insects and trees. This study highlights the importance of international collaboration in forest insect monitoring and surveillance programs to facilitate the early detection of novel associations as an important first step toward minimizing their impact.
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) | 0,001 | 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 ».