Managing for Elevated Yield of Moose in Interior Alaska
Notice bibliographique
Résumé
ABSTRACT Given recent actions to increase sustained yield of moose ( Alces alces ) in Alaska, USA, we examined factors affecting yield and moose demographics and discussed related management. Prior studies concluded that yield and density of moose remain low in much of Interior Alaska and Yukon, Canada, despite high moose reproductive rates, because of predation from lightly harvested grizzly ( Ursus arctos ) and black bear ( U. americanus ) and wolf ( Canis lupus ) populations. Our study area, Game Management Unit (GMU) 20A, was also in Interior Alaska, but we describe elevated yield and density of moose. Prior to our study, a wolf control program (1976–1982) helped reverse a decline in the moose population. Subsequent to 1975, moose numbers continued a 28‐year, 7‐fold increase through the initial 8 years of our study (λ B1 = 1.05 during 1996–2004, peak density = 1,299 moose/1,000 km 2 ). During these initial 8 hunting seasons, reported harvest was composed primarily of males ( = 88%). Total harvest averaged 5% of the prehunt population and 57 moose/1,000 km 2 , the highest sustained harvest‐density recorded in Interior Alaska for similar‐sized areas. In contrast, sustained total harvests of <10 moose/1,000 km 2 existed among low‐density, predator‐limited moose populations in Interior Alaska (≤417 moose/1,000 km 2 ). During the final 3 years of our study (2004–2006), moose numbers declined (λ B2 = 0.96) as intended using liberal harvests of female and male moose ( = 47%) that averaged 7% of the prehunt population and 97 moose/1,000 km 2 . We intentionally reduced high densities in the central half of GMU 20A (up to 1,741 moose/1,000 km 2 in Nov) because moose were reproducing at the lowest rate measured among wild, noninsular North American populations. Calf survival was uniquely high in GMU 20A compared with 7 similar radiocollaring studies in Alaska and Yukon. Low predation was the proximate factor that allowed moose in GMU 20A to increase in density and sustain elevated yields. Bears killed only 9% of the modeled postcalving moose population annually in GMU 20A during 1996–2004, in contrast to 18–27% in 3 studies of low‐density moose populations. Thus, outside GMU 20A, higher bear predation rates can create challenges for those desiring rapid increases in sustained yield of moose. Wolves killed 8–15% of the 4 postcalving moose populations annually (10% in GMU 20A), hunters killed 2–6%, and other factors killed 1–6%. Annually during the increase phase in GMU 20A, calf moose constituted 75% of the predator‐killed moose and predators killed 4 times more moose than hunters killed. Wolf predation on calves remained largely additive at the high moose densities studied in GMU 20A. Sustainable harvest‐densities of moose can be increased several‐fold in most areas of Interior Alaska where moose density and moose: predator ratios are lower than in GMU 20A and nutritional status is higher. Steps include 1) reducing predation sufficient to allow the moose population to grow, and 2) initiating harvest of female moose to halt population growth and maximize harvest after density‐dependent moose nutritional indices reach or approach the thresholds we previously published.
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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 | 0,000 |
| 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 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 ».