Identifying chemical compounds responsible for white-tailed deer (Odocoileus virginianus Zimmerman) browse resistance in northern white-cedar (Thuja occidentalis L.)
Notice bibliographique
Résumé
Northern white-cedar (Thuja occidentalis L.), also known as arborvitae or eastern white-cedar, is an important tree species with a wide range of economic, spiritual, and ecological benefits. Found throughout southeastern Canada and the northeastern United States, white-cedar is a slow-growing, shade-tolerant species capable of thriving in both upland and lowland environments, and on a variety of soil textures and drainage types. Since the mid-1900s, difficulties in natural regeneration have been observed for white-cedar in forested landscapes across its range. Several studies have attempted to investigate the forces underlying these difficulties. Browse by white-tailed deer (Odocoileus virginianus Zimmerman) has been identified as a probable cause for hindered white-cedar regeneration. Cedar serves as a winter shelter habitat for deer, as well as a preferred winter browse species. Interestingly, some cedar individuals are preferentially browsed by white-tailed deer, while other nearby trees are left untouched. However, knowledge about the interaction between white-tailed deer and northern whitecedar is limited, especially regarding the reasons for preferential browsing among cedar individuals. Therefore, we examined the role of plant-produced chemicals, known as phytochemicals, in the chemical ecology of white-cedar and white-tailed deer. Specifically, we employed two bioanalytical methodologies, solid-phase microextraction (SPME) gas chromatography-mass spectrometry (GC-MS) and thermal desorption GCMS, to identify compounds affecting deer browse activity. We compared the volatile chemical profiles of white-cedar that had and had not been browsed by white-tailed deer by analyzing both raw leaf material and methanol extracts of ground leaf material. Additionally, we established field-based plantings of white-cedar progeny from browsed and non-browsed parent trees, some of which being the trees that we collected leaf material from for the SPME and thermal desorption GC-MS analyses. We assessed deer browse activity on these white-cedar offspring using browse assessments and field camera traps in order to confirm the differential browsing among parent tree sources and evaluate the heritability of differential browsing traits. Using both SPME and thermal desorption GC-MS, we successfully identified 24 phytochemicals in white-cedar. Results from the quantification of four selected compounds (i.e., ?-terpinene, camphene, ?-terpinyl acetate, and thymol methyl ether) in white-cedar using SPME GC-MS indicated higher levels of all compounds in browsed vs non-browsed cedar, except camphene. Conversely, results from the thermal desorption GC-MS analysis revealed that one of these compounds, ?-terpinene, had significantly higher concentrations in the leaf material and methanol extracts for cedar that had not been browsed by deer. Furthermore, concentrations of ?-terpinene were found to be higher in methanol extracts of non-browsed white-cedar compared to browsed whitecedar when analyzed using thermal desorption GC-MS. Meanwhile, camphor and thymol methyl ether were found to have significantly higher concentrations in the methanol extracts from the browsed than the non-browsed white-cedar. Findings from the field-trial demonstrated higher browse presence and intensity on white-cedar progeny of non-browsed than browsed parentage. Furthermore, field camera video data revealed several instances in which individual cedar trees were browsed multiple times within the span of 24 hours, which may be an important topic of future research in studying deer browse behavior. This study demonstrates the first investigation targeting specific phytochemicals in the interaction of white-tailed deer and white-cedar. Our work provides a framework for integrating modern bioanalytical techniques and field trial validations in the targeted chemical profiling of white-cedar. Researchers and resource managers alike can build upon this framework to investigate the role of phytochemicals in the interaction of whitetailed deer and northern white-cedar to help conserve this important species.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».