Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/37492
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Optimising geopark networks for biodiversity conservation under climate change
Author(s): Vasiliev, Denis
Hamlet, Laura
Stevens, Rodney L
Bornmalm, Lennart
Hazlett, Richard W
Casadevall, Thomas
Duque, Carlos
Greenwood, Sarah
Contact Email: sarah.greenwood1@stir.ac.uk
Keywords: Geoheritage
Nature-based solutions
Biodiversity
Climatic refugia
Environmental economy
Sustainable development
Issue Date: Sep-2025
Date Deposited: 23-Sep-2025
Citation: Vasiliev D, Hamlet L, Stevens RL, Bornmalm L, Hazlett RW, Casadevall T, Duque C & Greenwood S (2025) Optimising geopark networks for biodiversity conservation under climate change. <i>Journal of Environmental Management</i>, 391, Art. No.: 126351. https://doi.org/10.1016/j.jenvman.2025.126351
Abstract: Geopark and geoheritage site networks are expanding globally, creating opportunities for sustainable development. Geoparks can deliver economic benefits through stimulation of tourism, making their establishment attractive to local governments and communities. However, the potential contribution of geoparks to sustainable development is not limited to socio-economic benefits. Geoparks, which are often in areas of geomorphic and soil variability, can contribute to biodiversity conservation and the provision of ecosystem services under climate change. These networks could play a pivotal role in biodiversity adaptation to global heating if designed and managed as climate-change refugia. Here we propose to optimise the value of geoparks and geoheritage sites as Nature-based Climate Solutions by considering them as part of the larger landscape and regional scale habitat networks, adjusting management practices and developing policy frameworks to better support Geoparks for biodiversity conservation.
DOI Link: 10.1016/j.jenvman.2025.126351
Rights: © 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Licence URL(s): http://creativecommons.org/licenses/by-nc-nd/4.0/

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