The direct and indirect effects of white-tailed deer on black-legged ticks
Notice bibliographique
Résumé
As a consequence of climate change, habitat degradation, and increased human-wildlife interaction, vector-borne zoonotic diseases have been emerging at unprecedented rates. In the Northern hemisphere, the most prevalent vector-borne disease is Lyme disease, which is transmitted by a tick vector. In Canada Lyme disease has emerged in recent decades and is projected to expand geographically. Currently, the areas of greatest concern within Canada are Ontario, Quebec, and Nova Scotia. In Eastern North America the Lyme disease pathogen is transmitted by black-legged ticks that depend on specific habitat characteristics, environment, and set of vertebrate hosts to complete their life cycle and establish. White-tailed deer are considered an essential host for reproduction of ticks although they are incompetent Lyme disease reservoirs. As an essential host, the direct effect of deer abundance on tick abundance has been well studied. Furthermore, white-tailed deer are keystone herbivores, and in high densities, their browsing has detrimental ecosystem impacts across multiple trophic levels. However, the indirect impact of deer browsing on tick abundance is not well known. Understanding both the direct and indirect effects of deer on tick abundance is essential for informing future management strategies aimed at reducing human disease risk. In this thesis, I first provide context on the emergence of Lyme disease in North America, with a focus on Quebec. I review the current knowledge on tick ecology, the historical and projected emergence and spread of the disease, and the role of white-tailed deer. Next, I investigate the direct and indirect impacts of deer on tick abundance at a UNESCO biosphere reserve located in Quebec. I measured deer abundance using motion-sensor camera traps, tick abundance by collection, and vegetation using deer exclosures at 15 sampling sites to determine the impact of deer browsing on vegetation, the effect of deer abundance on tick abundance, and the effect of vegetation on tick abundance. I found that within deer exclosures there was an increased number of plants, an increased mean plant height, and in one sector of the reserve, an increased number of plant species. Further, I found that tick abundance was not affected directly by deer abundance, but the number of ticks decreased with the number of plants, and more ticks were present inside the exclosures vs outside. I then discuss the implications of the observed patterns and propose future studies that would explore these further. To conclude, I outline how this study and proposed future studies can inform deer-targeted management strategies for reducing human disease risk, especially in nature parks where the potential for human-tick contact is heightened. First, I provide context on the emergence of Lyme disease in North America with a focus on Quebec. I review the tick ecology, the historical and projected emergence and spread of the disease, and the role of white-tailed deer. Next, I investigate the direct and indirect impacts of deer on tick abundance at a UNESCO biosphere reserve located in Quebec. I measured deer abundance using motion-sensor camera traps, tick abundance by collection, and vegetation using deer exclosures at 15 sampling sites to determine the impact of deer browsing on vegetation, the effect of deer abundance on tick abundance, and the effect of vegetation on tick abundance. I found that within deer exclosures there was an increased number of plants, an increased mean plant height, and in one sector of the reserve, an increased number of plant species. Further, I found that tick abundance was not affected by deer abundance or vegetation outside of the exclosure, but there were more ticks present inside the exclosures vs outside. I then discuss the implications of the observed effects and propose future studies that would explore these further. To conclude, I outline how this study and proposed future studies can inform deer-targeted management strategies for reducing human disease risk, especially in nature parks where the potential for human-tick contact is heightened
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».