Mitigating the Effects of Human Activity on Grizzly Bears (Ursus arctos) in Southwestern Alberta.
Notice bibliographique
Résumé
Anthropogenic habitat loss and alteration, as well as human-caused mortalities associated with increasing access, threaten grizzly bear populations across much of their North American range. This research investigates strategies for mitigating the negative effects of human activities on grizzly bears in southwestern Alberta. First, an optimization approach was used to prioritize sites for both protection and restriction while also considering landscape composition. Seasonal habitats where bears forage were balanced against proximity to roads, which are associated with mortality risk, to identify priority source- (high quality, low risk) and sink-like (high quality, high risk) habitats. Most sink-like sites (63%) were associated with unimproved roads or truck trails and are the best candidates for decommissioning and restoration efforts. Approximately 75% of priority source-like sites are currently unprotected, and overlap between protected areas and source-like sites was geographically biased. Second, the viability of using wildlife habitat enhancements to increase local food supply for grizzly bears in clearcuts was assessed. Specifically, I conducted planting trials of seedlings (plugs) for three important late-season fruiting shrubs and monitored their survival and growth over two growing seasons. The effects of soil nutrient amendments, exclosures, initial seedling condition, and environmental factors (elevation and terrain) on seedling growth were considered. A. alnifolia had the highest survival rate, although may not be as effective as S. canadensis and V. membranaceum in the long term due to browse preferences. Soil nutrient amendments reduced survival rates, whereas exclosures increased survival rates. Survival rates for S. canadensis and A. alnifolia along elevation gradients were inconsistent with expected niche spaces for both species, suggesting that knowledge of their natural niche spaces along the elevation gradient alone may not be sufficient to identify sites where they have the greatest chances of success. Management of sustainable grizzly bear populations should include measures that reduce the negative effects of human activities. Access management will be a critical component of this, and should be prioritized to areas where conflicts are most likely to occur, or to proactively protect secure, high quality habitats. As the prevalence of natural forest openings continues to decline, wildlife habitat enhancements in disturbed areas with open canopies, including forest harvests, have the potential to locally increase late-season food supply for grizzly bears and should be further explored.
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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 | 0,001 | 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 ».