Diet and habitat selection of gray wolves (Canis lupus) during the boreal caribou (Rangifer tarandus caribou) calving season in the southern Northwest Territories
Notice bibliographique
Résumé
Understanding the dietary habits of a species is crucial for studying ecosystem dynamics, and it becomes particularly important to understand the role of predators when prey populations become threatened. Prey are affected by predators via direct predation, indirectly through trophic cascades, and ultimately through the element of fear which influences the behaviour of prey. As an opportunistic predator, the gray wolf (Canis lupus) will often consume prey that are both numerous and vulnerable; however, wolves also adapt their diet and focus hunting efforts on ungulate prey in most of their range. Wolves are territorial, have large yearly home ranges, and become central place foragers during the denning period when pups are less mobile, often seeking habitats of higher quality to access valuable resources. The distribution of prey, den site selection, shelter, and anthropogenic features are all factors that may influence both diet and habitat selection of wolves. Therefore, my main objectives were to: 1) examine the diet of wolves in the southern Northwest Territories, Canada during the boreal caribou (Rangifer tarandus caribou) calving period as they are considered a threatened species and 2) develop habitat selection models using resource selection functions for wolves during both the denning period and annually. For my diet analyses, I used two methods: macroscopic and genetic approaches to examine the variation in diet at den sites from 2016-2020. Beaver (Castor canadensis) was the main prey in both frequency of occurrence and biomass consumed from the macroscopic analysis. White-tailed deer (Odocoileus virginianus) was the main prey by frequency of occurrence and moose (Alces alces) composed the largest portion by biomass with the genetic analysis. Habitat selection models were developed using data combined from 16 wolves tracked by satellite telemetry from 2016-2021. I analysed habitat selection in two groups of wolves: those associated with a den and those not associated with a den. For denning wolves, the top-performing model was the combined model, indicating selection for broadleaf-dense forests, non-vegetated areas, mixed wood-dense forests, steeper slopes, lower densities of linear features, proximity to roads, proximity to water, lower elevations, and avoidance of human settlements. For non-denning wolves, the top-performing model was also the combined model, indicating selection for mixed-wood-open forests, broad-leaf-open forests, mixed-wood-dense forests, higher densities of linear features, steeper slopes, proximity to human settlements, lower elevations, proximity to water, and proximity to roads. Although the diet analysis did not indicate that boreal caribou is highly prevalent prey for wolves in the southern NT, my habitat selection analysis during the denning period did align with preferred caribou habitat, suggesting spatial overlap between wolves and caribou that could increase encounter rates. This study will inform wildlife managers about habitat selection by wolves and possible impacts on prey.
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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 | 0,000 | 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 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 ».