Quantifying tourism booms and the increasing footprint in the Arctic with social media data

English version

Autoři: Claire A. Runge ^aff001; Remi M. Daigle ^aff002; Vera H. Hausner ^aff001
Působiště autorů: Arctic Sustainability Lab, Department of Arctic and Marine Biology, UiT The Arctic University of Norway, Tromsø, Norway ^aff001; Département de biologie, 'Université Laval, Québec, Canada ^aff002
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0227189

Souhrn

Arctic tourism has rapidly increased in the past two decades. We used social media data to examine localized tourism booms and quantify the spatial expansion of the Arctic tourism footprint. We extracted geotagged locations from over 800,000 photos on Flickr and mapped these across space and time. We critically examine the use of social media as a data source in data-poor regions, and find that while social media data is not suitable as an early warning system of tourism growth in less visited parts of the world, it can be used to map changes at large spatial scales. Our results show that the footprint of summer tourism quadrupled and winter tourism increased by over 600% between 2006 and 2016, although large areas of the Arctic remain untouched by tourism. This rapid increase in the tourism footprint raises concerns about the impacts and sustainability of tourism on Arctic ecosystems and communities. This boom is set to continue, as new parts of the Arctic are being opened to tourism by melting sea ice, new airports and continued promotion of the Arctic as a ‘last chance to see’ destination. Arctic societies face complex decisions about whether this ongoing growth is socially and environmentally sustainable.

Klíčová slova:

Airports – Conservation science – Data management – Ecosystems – Roads – Social media – Sustainability science – Winter

Zdroje

1. Maher PT. Tourism Futures in the Arctic. In: Latola K, Savela H, editors. The Interconnected Arctic—UArctic Congress 2016. Cham: Springer International Publishing; 2017. pp. 213–220. doi: 10.1007/978-3-319-57532-2_22

2. Fay G, Karlsdóttir A. Social indicators for Arctic tourism: observing trends and assessing data. Polar Geogr. 2011;34: 63–86. doi: 10.1080/1088937X.2011.585779

3. Scott D, Gössling S. What could the next 40 years hold for global tourism? Tour Recreat Res. 2015;40: 269–285. doi: 10.1080/02508281.2015.1075739

4. Lemelin H, Dawson J, Stewart EJ, Maher P, Lueck M. Last-chance tourism: the boom, doom, and gloom of visiting vanishing destinations. Curr Issues Tour. 2010;13: 477–493. doi: 10.1080/13683500903406367

5. Pashkevich A, Stjernström O, Lundmark L. Nature-based tourism, conservation and institutional governance: a case study from the Russian Arctic. Polar J. 2016;6: 112–130. doi: 10.1080/2154896X.2016.1171000

6. Kidd A, Monz CA, Hausner VH, Schmidt JI, Clark D. Nature-based tourism, resource dependency, and resilience of Arctic communities: Framing complex issues in a changing environment. J Sustain Tour. Forthcoming; doi: 10.1080/09669582.2019.1612905

7. Brandt JS, Buckley RC. A global systematic review of empirical evidence of ecotourism impacts on forests in biodiversity hotspots. Curr Opin Environ Sustain. 2018;32: 112–118. doi: 10.1016/j.cosust.2018.04.004

8. Becken S, Patterson M. Measuring national carbon dioxide emissions from tourism as a key step towards achieving sustainable tourism. J Sustain Tour. 2006;14: 323–338. doi: 10.2167/jost547.0

9. Tolvanen A, Kangas K. Tourism, biodiversity and protected areas–review from northern Fennoscandia. J Environ Manage. 2016;169: 58–66. doi: 10.1016/j.jenvman.2015.12.011 26720330

10. Leung D, Law R, Hoof H van, Buhalis D. Social media in tourism and hospitality: a literature review. J Travel Tour Mark. 2013;30: 3–22. doi: 10.1080/10548408.2013.750919

11. García-Palomares JC, Gutiérrez J, Mínguez C. Identification of tourist hot spots based on social networks: A comparative analysis of European metropolises using photo-sharing services and GIS. Appl Geogr. 2015;63: 408–417. doi: 10.1016/j.apgeog.2015.08.002

12. Levin N, Lechner AM, Brown G. An evaluation of crowdsourced information for assessing the visitation and perceived importance of protected areas. Appl Geogr. 2017;79: 115–126. doi: 10.1016/j.apgeog.2016.12.009

13. Walden-Schreiner C, Rossi SD, Barros A, Pickering C, Leung Y-F. Using crowd-sourced photos to assess seasonal patterns of visitor use in mountain-protected areas. Ambio. 2018; 1–13. doi: 10.1007/s13280-018-1020-4 29435731

14. Kim Y, Kim C, Lee DK, Lee H, Andrada RIIT. Quantifying nature-based tourism in protected areas in developing countries by using social big data. Tour Manag. 2019;72: 249–256. doi: 10.1016/j.tourman.2018.12.005

15. Wood SA, Guerry AD, Silver JM, Lacayo M. Using social media to quantify nature-based tourism and recreation. Sci Rep. 2013;3: 2976. doi: 10.1038/srep02976 24131963

16. Mancini F, Coghill GM, Lusseau D. Using social media to quantify spatial and temporal dynamics of nature-based recreational activities. PLOS ONE. 2018;13: e0200565. doi: 10.1371/journal.pone.0200565 30011294

17. Hale BW. Mapping potential environmental impacts from tourists using data from social media: a case study in the Westfjords of Iceland. Environ Manage. 2018;62: 446–457. doi: 10.1007/s00267-018-1056-z 29736767

18. Zanten BT van Berkel DBV, Meentemeyer RK Smith JW, Tieskens KF Verburg PH. Continental-scale quantification of landscape values using social media data. Proc Natl Acad Sci. 2016; 201614158. doi: 10.1073/pnas.1614158113 27799537

19. Oteros-Rozas E, Martín-López B, Fagerholm N, Bieling C, Plieninger T. Using social media photos to explore the relation between cultural ecosystem services and landscape features across five European sites. Ecol Indic. 2017; doi: 10.1016/j.ecolind.2017.02.009

20. Hausmann A, Toivonen T, Slotow R, Tenkanen H, Moilanen A, Heikinheimo V, et al. Social media data can be used to understand tourists’ preferences for nature-based experiences in protected areas. Conserv Lett. 2018;11: e12343. doi: 10.1111/conl.12343

21. Barchiesi D, Moat HS, Alis C, Bishop S, Preis T. quantifying international travel flows using Flickr. PLOS ONE. 2015;10: e0128470. doi: 10.1371/journal.pone.0128470 26147500

22. Stewart EJ, Draper D. Sustainable cruise tourism in Arctic Canada: an integrated coastal management approach. J Tour Manag. 2006;3: 77–88. doi: 10.3727/154427306779435210

23. Lamers M, Pashkevich A. Short-circuiting cruise tourism practices along the Russian Barents Sea coast? The case of Arkhangelsk. Curr Issues Tour. 2015;21: 440–454. doi: 10.1080/13683500.2015.1092947

24. Amundsen H. Illusions of Resilience? An analysis of community responses to change in Northern Norway. Ecol Soc. 2012;17. Available: https://www.jstor.org/stable/26269221

25. Lasserre F, Têtu P-L. The cruise tourism industry in the Canadian Arctic: analysis of activities and perceptions of cruise ship operators. Polar Rec. 2015;51: 24–38. doi: 10.1017/S0032247413000508

26. Stewart EJ, Dawson J, Draper D. Cruise tourism and residents in Arctic Canada: development of a resident attitude typology. J Hosp Tour Manag. 2011;18: 95–106. doi: 10.1375/jhtm.18.1.95

27. Panteras G, Wise S, Lu X, Croitoru A, Crooks A, Stefanidis A. triangulating social multimedia content for event localization using Flickr and Twitter. Trans GIS. 2014;19: 694–715. doi: 10.1111/tgis.12122

28. Albuquerque JP de, Herfort B, Brenning A, Zipf A. A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management. Int J Geogr Inf Sci. 2015;29: 667–689. doi: 10.1080/13658816.2014.996567

29. Gao Y, Wang S, Padmanabhan A, Yin J, Cao G. Mapping spatiotemporal patterns of events using social media: a case study of influenza trends. Int J Geogr Inf Sci. 2018;32: 425–449. doi: 10.1080/13658816.2017.1406943

30. Helwig NE, Gao Y, Wang S, Ma P. Analyzing spatiotemporal trends in social media data via smoothing spline analysis of variance. Spat Stat. 2015;14: 491–504. doi: 10.1016/j.spasta.2015.09.002

31. Goswami A, Kumar A. A survey of event detection techniques in online social networks. Soc Netw Anal Min. 2016;6: 107. doi: 10.1007/s13278-016-0414-1

32. Oppermann M. Tourism space in developing countries. Ann Tour Res. 1993;20: 535–556. doi: 10.1016/0160-7383(93)90008-Q

33. Ma M, Hassink R. An evolutionary perspective on tourism area development. Ann Tour Res. 2013;41: 89–109. doi: 10.1016/j.annals.2012.12.004

34. Butler RW. The concept of a tourist area cycle of evolution: implications for management of resources. Can Geogr Géographe Can. 1980;24: 5–12. doi: 10.1111/j.1541-0064.1980.tb00970.x

35. Daigle R, Dunnington D. flickRgeotag v0.0.1. Zenodo. http://doi.org/10.5281/zenodo.1314717 [Internet]. 2018. Available: https://github.com/remi-daigle/flickRgeotag/tree/v0.0.1

36. Arctic Assessment and Monitoring Programme (AMAP). Boundary for AMAP working group of the Arctic Council [Internet]. 2017. Available: http://geo.abds.is/geonetwork/srv/eng/catalog.search#/metadata/9BB31CE7-9AE2-453D-9234-0BAEB5C8A33C

37. South A. rnaturalearth: world map data from Natural Earth. R package version 0.1.0. [Internet]. 2017. Available: https://CRAN.R-project.org/package=rnaturalearth

38. Meijer JR, Huijbregts MAJ, Schotten KCGJ, Schipper AM. Global patterns of current and future road infrastructure. Environ Res Lett. 2018;13: 064006. doi: 10.1088/1748-9326/aabd42

39. Conservation of Arctic Flora and Fauna (CAFF). Arctic protected areas– 2017 [Internet]. 2017. Available: http://geo.abds.is/geonetwork/srv/eng/catalog.search#/metadata/2e56ee1f-50a9-4983-88f4-edaa8588950d

40. UNEP-WCMC and IUCN. Protected Planet: The World Database of Protected Areas [Internet]. 2018. Available: www.protectedplanet.net

41. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. [Internet]. 2017. Available: http://www.R-project.org/

42. Wickam H. tidyverse: easily install and load the “tidyverse”. R package version 1.2.1. [Internet]. 2017. Available: https://CRAN.R-project.org/package=tidyverse

43. Pebesma E. Simple Features for R: Standardized support for spatial vector data. R J. 2018; Available: https://journal.r-project.org/archive/2018/RJ-2018-009/

44. Wood SN. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J R Stat Soc B. 2011;73: 3–36.

45. Schlieder C, Matyas C. photographing a city: an analysis of place concepts based on spatial choices. Spat Cogn Comput. 2009;9: 212–228. doi: 10.1080/13875860903121848

46. Cságoly Z, Sæþórsdóttir AD, Ólafsdóttir R. Tourism changing the edge of the wild. J Outdoor Recreat Tour. 2017;17: 1–8. doi: 10.1016/j.jort.2016.10.004

47. Fredman P, Tyrväinen L. Frontiers in nature‐based tourism. Scand J Hosp Tour. 2010;10: 177–189. doi: 10.1080/15022250.2010.502365

48. Girardin F, Fiore FD, Ratti C, Blat J. Leveraging explicitly disclosed location information to understand tourist dynamics: a case study. J Locat Based Serv. 2008;2: 41–56. doi: 10.1080/17489720802261138

49. Li L, Goodchild MF, Xu B. Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr. Cartogr Geogr Inf Sci. 2013;40: 61–77. doi: 10.1080/15230406.2013.777139

50. Tenkanen H, Di Minin E, Heikinheimo V, Hausmann A, Herbst M, Kajala L, et al. Instagram, Flickr, or Twitter: Assessing the usability of social media data for visitor monitoring in protected areas. Sci Rep. 2017;7. doi: 10.1038/s41598-017-18007-4 29242619

51. Groulx M, Lemieux C, Dawson J, Stewart E, Yudina O. Motivations to engage in last chance tourism in the Churchill Wildlife Management Area and Wapusk National Park: the role of place identity and nature relatedness. J Sustain Tour. 2016;24: 1523–1540. doi: 10.1080/09669582.2015.1134556

52. Atwood TC, Marcot BG, Douglas DC, Amstrup SC, Rode KD, Durner GM, et al. Forecasting the relative influence of environmental and anthropogenic stressors on polar bears. Ecosphere. 2016;7: e01370. doi: 10.1002/ecs2.1370

53. Halliday WD, Têtu P-L, Dawson J, Insley SJ, Hilliard RC. Tourist vessel traffic in important whale areas in the western Canadian Arctic: Risks and possible management solutions. Mar Policy. 2018;97: 72–81. doi: 10.1016/j.marpol.2018.08.035

Quantifying tourism booms and the increasing footprint in the Arctic with social media data

Souhrn

Klíčová slova:

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