This paper analyses and compares a set of case studies on ecosystem services (ES) mapping and assessment with the purpose of formulating lessons learned and recommendations. Fourteen case studies were selected during the EU Horizon 2020 “Coordination and Support Action” ESMERALDA to represent different policy- and decision-making processes throughout the European Union, across a wide range of themes, biomes and scales. The analysis is based on a framework that addresses the key steps of an ES mapping and assessment process, namely policy questions, stakeholder identification and involvement, application of mapping and assessment methods, dissemination and communication and implementation. The analysis revealed that most case studies were policy-orientated or gave explicit suggestions for policy implementation in different contexts, including urban, rural and natural areas. Amongst the findings, the importance of starting stakeholder engagement early in the process was confirmed in order to generate interest and confidence in the project and to increase their willingness to cooperate. Concerning mapping and assessment methods, it was found that the integration of methods and results is essential for providing a comprehensive overview from different perspectives (e.g. social, economic). Finally, lessons learned for effective implementation of ES mapping and assessment results are presented and discussed. Graphical Abstarcat in Fig. 1.

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.

The obligations of the EU Biodiversity Strategy 2020 create a need for mapping and assessment of the state of biodiversity, ecosystems and their services in all European member states. Europe’s nine Outermost Regions (ORs) and 25 Overseas Countries and Territories (OCTs) are mainly islands, scattered around the globe. These territories contain unique flora and fauna and encompass diverse ecosystems, from coral reefs to rainforests. These highly diverse ecosystems provide multiple relevant ecosystem services from local to global scale. To date, the ecosystem services concept has so far received little attention in European ORs and OCTs. Therefore, our aims were (1) to analyse the current state of ecosystem services mapping and assessment in Europe’s overseas territories, (2) to identify knowledge gaps in the context of ecosystem service research and application and (3) to provide recommendations for future research and policy directions to fill these gaps. We conducted a systematic review of scientific literature for each of the ORs and OCTs, screening 1030 publications. The analysis resulted in 161 publications referring to ES mapping and assessment, of which most were conducted in the European Caribbean (31%) and Pacific (21%) territories. Results show that many ORs and OCTs are still blank spots in terms of ecosystem service mapping and assessment and that, despite many biodiversity studies referring to species’ abundance, little has been published on ecosystem services. Our systematic review highlights theknowledge lacking on dealing with invasive species, which pose major threats to native island biodiversity, ecosystem functions and ecosystem services. Further, it discusses knowledge gaps in (1) translation of information on island biodiversity and ecosystem functions into ES; (2) geographical coverage of mapping studies in most ORs and OCTs; (3) the lack of standardised approaches and integrated assessments to map, assess and value ecosystem services. Based on these results, future research and policy priorities could be adapted in order to focus on filling these gaps. To overcome current environmental policy challenges, it is crucial to address the ongoing decline in biodiversity, rising climatic and anthropogenic pressures on ecosystems and to maintain a sustainable ES flow to safeguard human well-being. Ultimately, ES mapping and assessment efforts will form the knowledge base for well-informed decision-making to protect Europe’s vulnerable overseas areas.

Modelling ecosystem services (ES) has become a new standard for the quantification and assessment of various ES. Multiple ES model applications are available that spatially estimate ES supply on the basis of land-use/land-cover (LULC) input data. This paper assesses how different input LULC datasets affect the modelling and mapping of ES supply for a case study on Terceira Island, the Azores (Portugal), namely: (1) the EU-wide CORINE LULC, (2) the Azores Region official LULC map (COS.A 2018) and (3) a remote sensing-based LULC and vegetation map of Terceira Island using Sentinel-2 satellite imagery. The InVEST model suite was applied, modelling altogether six ES (Recreation/Visitation, Pollination, Carbon Storage, Nutrient Delivery Ratio, Sediment Delivery Ratio and Seasonal Water Yield). Model outcomes of the three LULC datasets were compared in terms of similarity, performance and applicability for the user. For some InVEST modules, such as Pollination and Recreation, the differences in the LULC datasets had limited influence on the model results. For InVEST modules, based on more complex calculations and processes, such as Nutrient Delivery Ratio, the output ES maps showed a skewed distribution of ES supply. Yet, model results showed significant differences for differences in all modules and all LULCs. Understanding how differences arise between the LULC input datasets and the respective effect on model results is imperative when computing model-based ES maps. The choice for selecting appropriate LULC data should depend on: 1) the research or policy/decision-making question guiding the modelling study, 2) the ecosystems to be mapped, but also on 3) the spatial resolution of the mapping and 4) data availability at the local level. Communication and transparency on model input data are needed, especially if ES maps are used for supporting land use planning and decision-making.

Current environmental resource management policies acknowledge the need to manage and conserve biodiversity. Sustaining good ecosystem conditions and ecosystem services (ES) is imperative at and across multiple spatial scales. The ES concept is a valuable tool to communicate the benefits that nature provides to people. In the Guiana Shield, neighbouring countries share landscapes and ecosystems, and therefore also the services they supply. This study presents the first spatial ES assessments at territorial level for Suriname and French Guiana. Expert-based ES supply matrices were used and analysed in combination with Land Use/Land Cover (LULC) data to compile ES capacity maps for the two territories. In comparison, both ES supply matrices showed a high degree of similarity – forest ecosystems scored the highest ES capacities, followed by aquatic and marine ecosystems. Agricultural and urban land cover showed weak to moderate capacities for ES supply. A statistical analysis revealed a 30% difference of the two matrix assessments. Expert scores given for ES in Suriname exceeded those in French Guiana, especially for urban LULC and planted forests. Sociodemographic factors such as age, gender and institutional environment were analysed to explain this difference. The diverging scores can also be attributed to the distribution and the degree of similarity of the different LULC types and, hence, ES capacities and different governance and institutional contexts of the assessments. Comparative evaluations are essential to understand the differences in perception of ES supply capacities and to underpin future knowledge-based bilateral conservation policies and funding decisions by governments and managers.