Some mechanisms underlying variation in vital rates of grizzly bears on a multiple use landscape
Notice bibliographique
Résumé
ABSTRACT Understanding factors that govern the abundance of organisms is fundamental to the science of ecology and important for conservation and management of species. I used temporal and spatial comparisons to test the influence of human industrial activity, huckleberry ( Vaccinium membranaceum ) productivity, and population density on grizzly bear ( Ursus arctos ) vital rates and population trends over a 32‐year period. Survival rates of adult and subadult males were 0.84 and 0.78, respectively, and lower than those of adult (0.93) or subadult females (0.96). Of the 31 bears that died while radio‐collared, 26 (84%) were killed by people. Of those killed by people, 11 (35%) were legally killed by hunters and 84% were deaths that occurred <120 m from a road. In the first decade of study (1979–1988) when salvage logging and gas exploration was intensive, bear density was relatively low, and huckleberry production was generally good, the population increased (λ = 1.074) with high survival rates of cubs (0.84) and yearlings (0.86) plus a high reproductive rate of 0.374. During the second decade (1989–1998) when there was little industrial activity and huckleberry production remained good, the population continued to grow (λ ≈ 1.06–1.08) because survival of all age classes remained high, but the reproductive rate declined to 0.257. Bear density reached its maximum (55.6 bears/1,000 km 2 excluding independent males) at the start of the third decade. During the third decade (1999–2010), there was little industrial activity, but huckleberry production declined dramatically and often completely failed. During the third decade the population declined (λ ≈ 0.955–0.980) as the reproductive rate dropped to 0.192 because of small litters (1.82), extended interbirth intervals (2.93, 3.44, and 4.22 years in decades 1, 2, and 3, respectively) and increased age of primiparity (6.60, 7.09, and 10.46 years in decades 1, 2, and 3, respectively). Adult female survival also declined likely because more females were without offspring and thus vulnerable to hunting. The best model predicting if a parous female would have a small (0 or 1 cub) or large (2 or 3 cub) litter when not encumbered with offspring the previous mating season included both huckleberry abundance the previous year and female bear density. Population inventories during the third decade had approximately twice as many bears detected per DNA hair trap set in the portion of the valley where there had been rapid industrial development, grizzly bear hunting, and large huckleberry fields than in an adjacent portion of the valley that was protected from industry and hunting but with no major huckleberry fields. The abundance of huckleberries growing in mountains above most human activity permitted this population to expand in spite of the industrial development. The population was primarily regulated by the interaction of bear density and the density‐independent production of huckleberries, their major summer‐fall energy food. © 2015 The Wildlife Society.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 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 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».