Mapping and assessing ecosystem services in the EU - Lessons learned from the ESMERALDA approach of integration

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Burkhard, B. et al.: Mapping and assessing ecosystem services in the EU - Lessons learned from the ESMERALDA approach of integration. In: One Ecosystem 3 (2018), e29153. DOI: https://doi.org/10.3897/oneeco.3.e29153

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Zum Zitieren der Version im Repositorium verwenden Sie bitte diesen DOI: https://doi.org/10.15488/4275

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The European Union (EU) Horizon 2020 Coordination and Support Action ESMERALDA aimed at developing guidance and a flexible methodology for Mapping and Assessment of Ecosystems and their Services (MAES) to support the EU member states in the implementation of the EU Biodiversity Strategy’s Target 2 Action 5. ESMERALDA’s key tasks included network creation, stakeholder engagement, enhancing ecosystem services mapping and assessment methods across various spatial scales and value domains, work in case studies and support of EU member states in MAES implementation. Thus ESMERALDA aimed at integrating various project outcomes around four major strands: i) Networking, ii) Policy, iii) Research and iv) Application. The objective was to provide guidance for integrated ecosystem service mapping and assessment that can be used for sustainable decision-making in policy, business, society, practice and science at EU, national and regional levels. This article presents the overall ESMERALDA approach of integrating the above-mentioned project components and outcomes and provides an overview of how the enhanced methods were applied and how they can be used to support MAES implementation in the EU member states. Experiences with implementing such a large pan-European Coordination and Support Action in the context of EU policy are discussed and recommendations for future actions are given.
Lizenzbestimmungen: CC BY 4.0 Unported
Publikationstyp: Article
Publikationsstatus: publishedVersion
Erstveröffentlichung: 2018
Die Publikation erscheint in Sammlung(en):Naturwissenschaftliche Fakultät

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Pos. Land Downloads
Anzahl Proz.
1 image of flag of Germany Germany 80 54,79%
2 image of flag of United States United States 29 19,86%
3 image of flag of China China 6 4,11%
4 image of flag of United Kingdom United Kingdom 3 2,05%
5 image of flag of Argentina Argentina 3 2,05%
6 image of flag of Netherlands Netherlands 2 1,37%
7 image of flag of Lithuania Lithuania 2 1,37%
8 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 2 1,37%
9 image of flag of France France 2 1,37%
10 image of flag of Switzerland Switzerland 2 1,37%
    andere 15 10,27%

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