Examing the Dynamic Relationship Between Climate Change and Tourism: A Case Study of Churchill's Polar Bear Viewing Industry
Notice bibliographique
Résumé
The purpose of this thesis research was to examine the dynamic relationship between climate change and tourism, with a direct focus on Churchill, Manitoba’s polar bear viewing industry. This unique tourism industry and the polar bears it depends on, are experiencing the negative effects of climate change due to warmer temperatures and melting sea ice, which significantly impacts the health, appearance, and prevalence of polar bears on display for tourists. Not only is this tourism industry affected by climate change, it also contributes to the ongoing changes of climatic conditions. This is due to the dependence of fossil fuel energy used for transportation, accommodation, and activities which directly contributes to the release of greenhouse gas emissions and thus to global climate change. Emissions from tourism has increased by 3% over the last 10 years, largely as a result of the accessibility and affordability of air travel, the most energy intensive form of transportation (Lenzen et al., 2018; UNWTO-UNEP-WMO, 2008). It has been suggested that in response to the increase in the demand to travel, the tourism industry should take a leadership role to reduce their total greenhouse gas emissions in an effort to decrease the impact of climate change. In this study, a visitor survey was conducted during four weeks of Churchill’s 2018 polar bear viewing season (October 16 to November 16). The aim of the survey was to: 1) estimate greenhouse gas emissions from polar bear viewing tourists and the polar bear viewing industry; 2) identify tourists’ awareness of the impacts of climate change (to and from tourism activities); 3) understand tourist’s climate-related travel motivations, and 4) identify tourists’ opinions on climate change mitigation strategies. Visitor surveys were hand- distributed at the Churchill Northern Studies Centre and at the Churchill Airport to tourists who had participated on a polar bear viewing tour. Surveys were analyzed and compared with the results from similar studies (Dawson et al., 2010 and Groulx, 2015) to identify the changing trends in greenhouse gas emissions, travel motivations, tourists’ knowledge of climate change, and acceptance of climate change mitigation strategies. Similar to trends observed 10 years ago, emissions from polar bear viewing tourists are 3-34 times higher than the average global tourist experience. Tourists’ awareness about climate change has stayed relatively consistent, despite the topic of climate change having received increased attention globally. Tourists recognize that climate change is happening and that it is human induced however, there is still a lack of understanding of how air travel is a contributor to climatic change. Although briefly mentioned in some participant’s responses, the main motivation was not to see a polar bear before it disappeared from the wild. The majority of tourists identified they were traveling to Churchill simply for the opportunity to see a polar bear. Additional motivators were photography, the Northern Lights, and for the opportunity to see other Arctic animals. The climate change mitigation strategies that tourists believed to be the most effective to reduce emissions were educational programs and transportation alternatives (such as taking the train- which was not an option at the time of study due to a rail line shutdown). This research contributes to the existing knowledge about tourism and climate change and provides a current analysis of Churchill’s polar bear viewing industry, enabling a comparison between findings from another study conducted over ten years ago. This research also makes conclusions about climate change mitigation strategies that might be effective for Churchill’s tourism industry to reduce their impact on the environment.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».