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Record W4412763761 · doi:10.1016/j.tfp.2025.100966

Changes in visitor behaviour in Canadian National Parks due to COVID-19: focusing on visitor spatial location and the distance between park facilities and visitors

2025· article· en· W4412763761 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTrees Forests and People · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaChinese Academy of Forestry
KeywordsVisitor patternCoronavirus disease 2019 (COVID-19)GeographyNational parkSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakEnvironmental resource managementEnvironmental scienceArchaeologyComputer scienceMedicineVirology

Abstract

fetched live from OpenAlex

• COVID-19 significantly reduced visitor numbers in Canadian National Parks. • Visitor spatial distribution shifted toward remote, less-populated park areas. • Distance to natural features outweighed proximity to hotels post-COVID-19. • Flickr geotagged data revealed long-term shifts in visitor behaviour. • Policy should support diversified tourism products adapted to new preferences. COVID-19 has significantly altered visitor behaviour in Canadian National Parks (NPs), which are largely composed of forested landscapes that support vital human–nature interactions. To investigate these changes, this study selected six NPs and examined shifts in spatial visitation patterns and their relationship with proximity to park facilities before and during the pandemic. Based on 48,041 geotagged Flickr photos from 2018 to 2023, we employed the Seasonal Concentration Index (SCI), Geographic Concentration Index (GCI), Kernel Density Estimation (KDE), and the Optimal Parameter-based Geographic Detector (OPGD). Temporally, all six NPs experienced a pronounced drop in visitor numbers in 2020–2021, with only partial recovery by 2023. Spatially, visitor distribution remained highly uneven, with hotspots clustered around Banff, Jasper, and Lake Louise. However, a gradual dispersion of visitor flow toward less-developed and lower-density areas was observed in recent years. Importantly, COVID-19 shifted visitors’ spatial preferences: proximity to natural features such as rivers became more influential than the traditional pull of accommodations and services. These findings suggest a pandemic-induced reconfiguration of tourism behaviour, favouring more dispersed and nature-oriented experiences, though not necessarily closer to forest interiors. The study underscores the need for adaptive tourism planning that aligns with changing recreational demands and the ecological character of NPs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.323
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it