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Population dynamics of reintroduced elk (Cervus elaphus) in eastern North America

2017· dissertation· en· W2735773277 sur OpenAlexfundaboutno aff
Jesse N. Popp

Notice bibliographique

RevueLu Zone Ul (Laurentian University) · 2017
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueWildlife Ecology and Conservation
Établissements canadiensnon disponible
Organismes subventionnairesNatural Sciences and Engineering Research Council of Canada
Mots-clésCervus elaphusGeographyPopulationForestryEcologyFisheryBiologyDemography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Studies that focus on identifying factors that influence reintroduction success have often taken an
\nindividual population approach; however, investigating multiple populations can provide
\nadditional insight. The overall objective of this research was to emphasize the value of using
\nwithin- and among-population approaches to identifying factors that influence the population
\ndynamics of a reintroduced species. Elk (Cervus elaphus), a species that was extirpated from
\neastern North America during the late 1800s, has been reintroduced to portions of its former
\nrange over the past century through several initiatives. Today, there are several established
\npopulations across eastern regions of the USA and Canada, for which extensive monitoring data
\nare available, creating an opportunity to investigate reintroduction success. I aimed to use these
\ndata to identify factors associated with changes in the survival and population growth rates of 10
\nreintroduced elk populations across eastern North America. More specifically, I: (1) performed a
\nliterature review detailing the history of elk reintroduction in eastern North America over the
\npast century, (2) identified factors associated with the variation in population growth rates
\n(reintroduction success) for 10 reintroduced elk populations using an among-population
\napproach, (3) identified and assessed how climate affected the population growth rates of 7
\nreintroduced elk populations, and (4) investigated direct causes of mortality (predation and train
\ncollisions) associated with a single elk population experiencing low population growth.
\nAlthough the number of successful elk restoration attempts has increased over the past century,
\nthere has been substantial variation in population growth rates among reintroductions. Major
\niv
\ncauses of elk mortality in restored populations differed between the pre- to post-acclimation
\nphases of reintroduction. Population growth rates were negatively related to the percentage of
\nconiferous forest within elk population range, suggesting that expansive areas of coniferous
\nforests in eastern North America may represent sub-optimal elk habitat.
\nThe Burwash elk population in Ontario had low growth rate compared to most other populations
\nreintroduced into eastern North America. Predation and train collisions were the most important
\nsource of mortality for this population. The number of annual elk-train collisions, as well as their
\nlocations, were monitored and recorded over 14 years. Collision locations were highly sitespecific
\nand were positively correlated to the proximity of bends in the railway. By relating the
\nnumber of annual elk-train collisions to various climate factors, I found that collision rates were
\npositively related to snow depth. By analyzing field camera data, I found that elk used the
\nrailway mostly during the fall and spring, when elk commonly travel to and from wintering
\ngrounds. However, by examining VHF telemetry locations, I determined that elk were closer to
\nthe railway in winter than in any other season. Railways likely are perceived by elk as easy travel
\ncorridors, especially in the winter, and deep snow might prevent escape from oncoming trains.
\nBlack bear (Ursus americanus) and wolves (Canis lupus) were the major predators of elk in the
\nBurwash population. White-tailed deer (Odocoileus virginianus), elk (Cervus elaphus), and
\nmoose (Alces alces), were the ungulate prey species available to both predators. To determine if
\npredators prefer one ungulate species over another, and to identify which predator species is
\nlikely to have a greater impact on elk survival, I investigated predator diets. To compare rates of
\nv
\nungulate use by predators in relation to prey availability, I calculated the relative abundance of
\neach ungulate species. I found that wolves used juvenile and adult elk as their primary ungulate
\nprey in greater proportions in comparison to their availability. Bears on the other hand, tended to
\nuse all ungulate species in proportion to their availability.
\nClimate is well known to affect ungulate population dynamics; however, several factors (e.g.:
\ndensity, predator presence), can govern the response. Relating the annual growth rates of 7 elk
\npopulations to various climate factors I found that responses were population specific. Increased
\nannual snow fall was associated with declines in population growth rates for 2 of the 7
\npopulations assessed and only 1 population responded negatively to increased summer
\ntemperatures. Climate likely interacts with other environmental variables to influence
\nfluctuations in annual population growth rates which warrants further investigation.
\nThe results of this research will contribute to informed planning of future elk reintroductions and
\nshould support development through improved management. In addition, this research highlights
\nthe importance of using within- and among- populations approaches to investigating factors that
\ninfluence elk reintroduction success.

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 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 candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
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 enseignants0,417
Score d'incertitude au seuil1,000

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 ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,006
Tête enseignante GPT0,193
Écart entre enseignants0,187 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2017
Routes d'admission2
Résumé présentoui

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