MétaCan
Menu
Retour à la cohorte
Enregistrement W1232149504

Status of moose populations and challenges to moose management in Fennoscandia.

2003· article· en· W1232149504 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

venuePublié dans une revue dont le pays d'attache est le Canada.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
Aucune affiliation canadienne. Une base fondée sur la seule affiliation (le devis habituel) n'aurait jamais vu ce travail. C'est l'un des travaux qui justifient l'inversion de la base.

Notice bibliographique

RevueAlces · 2003
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueWildlife Ecology and Conservation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGeographyEcological successionPopulation densityHabitatPopulationEcologyPopulation declinePhysical geographyBiologyDemography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

In the Fennoscandian countries, Norway, Sweden, and Finland, moose (Alces alces) populations began to increase rapidly in the 1960s and have since then been among the most productive and heavily harvested moose populations in the world. At the start of the 20th century, the total annual harvest was < 10,000 moose, whereas in 2000, the annual kill reached about 200,000. The winter population was estimated to be about 500,000. In Sweden and Finland, the highest harvest numbers (and presumably population density) were recorded in the first half of the 1980s and in Finland again in the late 1990s and during the beginning of the 2000s. In Norway, the 1990s was the decade of the highest harvest numbers. The current regional moose density during winter varies from < 0.2 to about 2 moose/km2 within Fennoscandia. Locally, the density may far exceed this level in typical wintering areas (e.g., 5-6 moose/km2). In general, the current densities are lower in the north than in the south and higher in Norway and Sweden than in Finland. The strong increase in harvest and the present high densities are explained by several factors. First, modern forestry clear-cutting practices have provided Fennoscandian moose with prime habitats in the form of early succession stages. Accordingly, the current carrying capacity is likely to be relatively high compared to the situation 50-100 years ago. The current trend, however, is towards less activity in the forest and a decreasing proportion of forests found at an early successional stage. This may increase the food limitation already seen in several populations; i.e., in all three countries, body mass and recruitment rates have been found to decrease with increasing density. Second, the introduction of sex and age-specific harvesting in the early 1970s has increased the general productivity of the populations. By focusing the harvest on calves, yearlings, and adult males, the proportion of productive females, the mean age of females, and the annual recruitment rate have increased. Simultaneously, the proportion and mean age of males have decreased, and in some populations, this has been associated with delayed parturition dates and lower fecundity; i.e., due to inadequate number of males for timely reproduction. Third, mortality other than hunting is low, and only near the eastern border of Finland with Russia has predation by wolves and bears had a notable effect on productivity figures. This situation is about to change with increasing populations of large carnivores in all of Fennoscandia during the 1990s. The management principles have been quite similar within Fennoscandia, although differences in legislation have resulted in national and regional differences in management performance. In general, moose managers take advantage of data collected by hunters during the hunting season (e.g., hunting statistics, number, sex, and age of moose observed) to monitor population development and determine hunting quotas. Moreover, in all three countries, the issues of traffic accidents and damage to forestry and agriculture play a central role in moose management and discussions concerning optimum population sizes. ALCES VOL. 39: 109-130 (2003)

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil0,198

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,041
Tête enseignante GPT0,262
Écart entre enseignants0,221 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle