Polar Bear (<i>Ursus maritimus</i>) Life History and Population Dynamics in a Changing Climate
Notice bibliographique
Résumé
There is now an increasing body of scientific evidence that rapid changes in the earth’s climate over the last half-century are influencing the physiology, phenology, distribution, and abundance of species (Hughes, 2000; McCarty, 2001; Stenseth et al., 2002; Root, 2003). As a result, understanding how climate change will affect the distribution and abundance of species has become a major concern in ecology. Among long-lived vertebrates, environmental variation is known to influence growth (Post et al., 1997), survival (Gaillard et al., 1997), reproductive success (Albon et al., 1983), and consequently the demography of populations. Although large-scale patterns of climatic variability such as the El Nino Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) are known to influence the life history and population dynamics of both marine and terrestrial species (Stenseth et al., 2002), relatively little information exists on how rapidly occurring but persistent change in the earth’s climate (i.e., global warming) will affect species life-history traits and population dynamics. The research I am conducting for my PhD will examine how environmental variation influences the life-history traits and population dynamics of a large carnivore species, the polar bear (Ursus maritimus), through climate-mediated shifts in the availability of essential prey resources. Polar bear life history is intimately linked to the sea ice environment, with sea ice providing the platform from which bears hunt, travel, mate, and in some areas, den (Amstrup, 2003). Over the last 20 years, in association with climate warming, there have been significant declines in both the temporal and spatial extent of sea ice cover in the Arctic (Parkinson and Cavalieri, 1989; Parkinson et al., 1999; Comiso, 2002; Comiso and Parkinson, 2004; Stroeve et al., 2007). It has been suggested that spatial and temporal changes in the sea ice environment will result in reduced availability and abundance of the polar bears’ primary prey, seals (Derocher et al., 2004). In turn, reduced prey availability has the potential to influence the life history of individuals (growth, reproduction, and survival) and thereby the population dynamics of polar bears. The effects of reduced prey availability are already evident in western Hudson Bay, where polar bears are forced ashore during an extensive icefree period that can last for up to four months each summer. Higher air temperatures and earlier sea ice breakup in spring have extended this period and resulted in significant declines in the body mass of adult female polar bears (Stirling et al., 1999; Stirling and Parkinson, 2006). Sea ice– mediated changes in individual phenotypic quality have the potential to influence a number of individual life history traits (e.g., age at first reproduction, litter size, and longevity), all of which can influence the demography of polar bear populations. The purpose of my PhD research is to determine to what extent changes in the Arctic sea ice environment are influencing the growth, reproduction, and survival of polar bears and how changes in key life history traits and vital rates are influencing polar bear population dynamics.
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 | 0,000 | 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 | 0,000 | 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 ».