Valuing Protected Area Tourism Ecosystem Services Using Big Data.
Economic value from protected areas informs decisions for biodiversity conservation and visitor benefits. Calculating these benefits assists governments to allocate limited budget resources. This study estimated tourism ecosystem service expenditure values for a regional protected area network in So...
| Published in: | Environmental Management Vol. 71; no. 2; pp. 260 - 274 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Published: |
Springer Nature
Feb2023
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=161655314&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 161655314 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0364152X O5H jtl: Environmental Management issn: 0364152X maglogo: N pubinfo: dt: Feb2023 vid: 71 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 161655314 160274973 10.1007/s00267-022-01746-0 161655314 ppf: 260 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Valuing Protected Area Tourism Ecosystem Services Using Big Data. aug: au: Loch, Adam Scholz, Glen Auricht, Christopher Sexton, Stuart O'Connor, Patrick Imgraben, Sarah affil: Centre for Global Food and Resources, School of Economics and Public Policy, Level 6 - 10 Pulteney Street, The University of Adelaide, Adelaide, SA, Australia sug: ab: Economic value from protected areas informs decisions for biodiversity conservation and visitor benefits. Calculating these benefits assists governments to allocate limited budget resources. This study estimated tourism ecosystem service expenditure values for a regional protected area network in South Australia (57 parks) using direct transactional data, travel costs and economic multipliers. The big dataset came from a comprehensive booking system, which helped overcome common limitations associated with survey data (e.g., key areas rather than full network and high zero-value observations). Protected areas returned AU$373.8 million in the 2018–19 base year to the South Australian economy. The results indicate that combined estimation methods coupled to big data sets provide information on baseline expenditure to engage with critical conservation and tourism sites (e.g., Kangaroo Island). In this case they offer a unique full area network expenditure estimate which is an improvement on typical survey approaches, highlighting the advantage of protected area managers investing in big data. Finally, as South Australian protected areas exceed that in many other contexts the study offers important inputs to funding narratives and protected area expansion in line with global assessment targets. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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