The relative impacts of recreational activity and landscape protection on a Rocky Mountain mammal community
Notice bibliographique
Résumé
Modern human expansion and landscape development has substantially restructured natural landscapes with cascading impacts on biodiversity, resulting in population declines and range contractions in many North American large mammal species. While conservation efforts through the establishment of protected areas (PA) mitigate stressors to wildlife by preventing further landscape disturbance, mammals are still impacted by high human use within PA, and ongoing landscape development outside PA boundaries. Comprised of a network of PA and unprotected areas, Canada’s Rocky Mountains provide important habitat to a rich mammal community. The Rocky Mountains also support a range of human uses, including industrial development creating ongoing landscape disturbance, and recreational use of landscape features such as trails and roads. The relative importance of PAs in supporting mammal populations, as well as the impacts of recreational landscape use to mammals, are not well understood. In this thesis, I used wildlife camera arrays to investigate the relative impacts of recreation and landscape protection on a Rocky Mountain mammal community, assessing distributions of six species: wolves, grizzly bears, coyote, black bears, white-tailed deer, and mule deer. I chose to assess multiple species as species are expected to respond differently to disturbance, with wolves and grizzly bears being disturbance-sensitive while coyotes and white-tailed deer are more disturbance-tolerant. In my second chapter, within an unprotected region, I investigated whether motorized recreation influenced mammal distributions, weighing its importance against landscape disturbance, and natural landscape features. I found that wolves avoided areas of high motorized use; coyote, white-tailed deer, and grizzly bears were better explained by landscape disturbance features, and black bears and mule deer were best explained by natural landscape features. Recreational use can cause spatial displacement of wildlife, with the effect being constrained to more disturbance-sensitive species such as wolves. These results have important implications in managing habitat for disturbance sensitive species, but also emphasize the importance of minimizing and restoring ongoing landscape disturbance, as disturbance facilitates recreational use, and ultimately has a larger impact on the greater mammal community. In my third chapter, I investigated whether protected areas outweigh natural or anthropogenic landscape features in explaining species occurrence, across a range of PA and unprotected areas in the Rocky Mountains. I found that PAs best explained the occurrence of four out of six species: wolves, grizzly bears, coyote, and mule deer. Wolves, grizzly bears, and mule deer had positive associations with PAs, while coyotes had negative associations. Black bears, white-tailed deer, and mammal diversity were best explained by anthropogenic landscape disturbance. These results underscore the importance of PAs in providing habitat for disturbance-sensitive predators, and demonstrate that anthropogenic landscape management and alteration are driving factors in determining species distributions. This research has important implications for future landscape management. For disturbance-sensitive species, such as wolves, limiting the extent of motorized recreation is important; on a broader scale, the establishment of PAs is important for providing habitat for disturbance-sensitive top predator species, and ultimately reducing ongoing landscape alteration and restoring habitat is essential to mitigate ongoing impacts to mammal communities.
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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 | 0,001 |
| 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».