Spalding Mark D, Longley-Wood Kate, McNulty Valerie Pietsch, Constantine Sherry, Acosta-Morel Montserrat, Anthony Val, Cole Aaron D, Hall Giselle, Nickel Barry A, Schill Steven R, Schuhmann Peter W, Tanner Darren
The Nature Conservancy, Protect Oceans Land and Water Program, Strada delle Tolfe, 14, Siena, 53100, Italy; Conservation Science Group, Department of Zoology, University of Cambridge, Cambridge, CB2 3QZ, UK.
The Nature Conservancy, Protect Oceans Land and Water Program, 99 Bedford St, Boston, MA, 02111, USA.
J Environ Manage. 2023 Jul 1;337:117696. doi: 10.1016/j.jenvman.2023.117696. Epub 2023 Mar 17.
The ability to quantify nature's value for tourism has significant implications for natural resource management and sustainable development policy. This is especially true in the Eastern Caribbean, where many countries are embracing the concept of the Blue Economy. The utilization of user-generated content (UGC) to understand tourist activities and preferences, including the use of artificial intelligence and machine learning approaches, remains at the early stages of development and application. This work describes a new effort which has modelled and mapped multiple nature dependent sectors of the tourism industry across five small island nations. It makes broad use of UGC, while acknowledging the challenges and strengthening the approach with substantive input, correction, and modification from local experts. Our approach to measuring the nature-dependency of tourism is practical and scalable, producing data, maps and statistics of sufficient detail and veracity to support sustainable resource management, marine spatial planning, and the wider promotion of the Blue Economy framework.
量化自然对旅游业的价值的能力对自然资源管理和可持续发展政策具有重大影响。在东加勒比地区尤其如此，那里许多国家正在接受蓝色经济的概念。利用用户生成内容（UGC）来了解游客活动和偏好，包括使用人工智能和机器学习方法，仍处于开发和应用的早期阶段。这项工作描述了一项新的努力，该努力对五个小岛屿国家旅游业的多个依赖自然的部门进行了建模和绘图。它广泛使用了用户生成内容，同时认识到挑战，并通过当地专家的大量投入、纠正和修改来加强该方法。我们衡量旅游业对自然的依赖程度的方法是切实可行且可扩展的，能够生成足够详细和准确的数据、地图及统计信息，以支持可持续资源管理、海洋空间规划以及更广泛地推广蓝色经济框架。
