Mapping and assessing ecosystems and their services (ES) is core to the EU Biodiversity (BD) Strategy 2020 (Maes et al. 2016). Specifically, Action 5 of the Strategy’s Target 2 sets the requirement for an EU-wide knowledge base developed by Member States designed to be: “a primary data source for developing Europe’s green infrastructure; a resource to identify areas for ecosystem restoration; and, a baseline against which the goal of ‘no net loss of BD and ES’ can be evaluated" (Burkhard et al. 2018).

In response to these requirements, ESMERALDA (Enhancing ecoSysteM sERvices mApping for poLicy and Decision mAking) aims to deliver a flexible methodology to provide the building blocks for pan-European and regional assessment. The work supports the timely delivery of EU Member States in relation to Action 5 of the BD Strategy and the needs of assessments in relation to the requirements for planning, agriculture, climate, water and nature policy. While other overviews of ecosystem services methods classification exist (Harrison et al. 2018), the focus in this paper is on how these methods have been applied for mapping and assessing studies rather than adding a new classification. The creation of a database for existing studies is considered an essential step in finding the method most suited to a specific issue or problem where mapping and assessing ecosystems is at the core (ESMERALDA 2017). The ‘method finder’ that has been developed is an online tool which is described in Reichel and Klug (this volume). The ESMERALDA database and method identification described here focuses instead on the ongoing activities in Europe such as MAES (https://biodiversity.europa.eu/maes), OpenNESS (http://www.openness-project.eu/), OPPLA (https://oppla.eu/) and other national studies such as UK NEA (http://uknea.unep-wcmc.org/) or Spanish NEA (http://www.ecomilenio.es/). The methods for mapping and assessing ecosystems and their services described here are enhanced by the creation of this operational database which integrates biophysical, social and economic mapping and assessment methods for ES. The results will be useful for designing specific case study applications for ecosystems and to identify gaps in mapping and assessment activities of ES in Europe.

Methods

Geographical distribution and ecosystem types

Altogether, 28 countries within Europe were part of the database (this included 2 Baltic and 2 western Balkan countries, linked via regional hubs). The analysis indicated that ES mapping and assessments have been conducted in 26 countries (Fig. 5). Several ES studies have been undertaken in the United Kingdom (47 method examples), Germany (36), Poland (32) and Spain (31). It is evident that most case studies come from countries for which a National Ecosystem Assessment has been already performed (e.g. UK NEA, Spanish NEA, NEA-D).

The examples included in the database cover all ecosystem types as indentified in MAES (Maes et al. 2014). While ‘Woodland and Forest’ examples dominate (16%), it is fair to say that all ecosystem types are included and well-studied. Again, multiple entries were possible.

Of the 370 studies included in the database, 351 were written in English. However, we also encouraged national studies and hence the remaining 19 are written in Dutch (6), Polish (4), Slovenian (3), Hebrew (3), Swedish (2) and French (1). Most have an English abstract. We wanted to leave the opportunity open for national case studies to also be available for EU members states and the national MAES project. The variation in the language, however, does not reflect any bias but only reflects the background of the consortium members whohave submitted material.

Spatial Scales and sources of data

Most of the method applications (91%) focused on one scale in their study only, while 9% studies covered multiple scales. In total, the ‘Regional scale’ (43%) was the most commonly used (Fig. 6). Local studies (27%) were also well represented.

Regarding the nature of studies, 44% were classified as assessment, while 31% were purely focused on mapping. 'Mapping' stands for the spatial delineation of ecosystems as well as the quantification of their condition and the services they supply, while 'assessing' refers to the translation of scientific evidence into information that is understandable for policy and decision-making. Based on these definitions, 25% of the studies used a combination of mapping and assessment methods (Fig. 7).

The majority of sources of the database come from published scientific papers (292), 41 came from grey literature (reports) and 37 from case studies. It should be noted that, if a case study was written up as a scientific paper, it was coded as ‘scientific literature’ and, if it was available as a report on a website, then it was coded as ‘grey literature’. Hence, the coding followed the easiest access to the information and so avoided double counting.

Responders to the online questionnaire were also asked which data were used and how these data are available. In most examples, GIS data formed the basis for the investigation, followed by statistical data (Fig. 8).

Mapping and assessment methods and ES classification systems

When looking at the ‘Domains of the method’, studies were classified into ‘biophysical’*2, ‘social’*3 and ‘economic’*4; multiple options were also possible. As a result, 53% of the studies worked only within the biophysical domain, while those with social (18%) and economic (19%) accounted for less than half of the studies (Fig. 9). Further examination of the results shows that biophysical methods are the most common methods used (i.e. spatial proxy methods), followed by economic methods (i.e. choice modelling or value transfer) and social methods are still the least used types of methods (i.e. preference assessment) (Fig. 10).

Another question and requirement to describe the entry was ‘which ecosystem service classification system’ was used? While the adopted framework was described in MAES and in ESMERALDA CICES version 4.3. , we did not want to exclude valid information that used methods linked to different classification systems. As Figure 10 shows, a slight majority of entries is based on the MA classification, followed by CICES (77) and TEEB (40). While 40 used a different or slightly adjusted system, in 120 cases, no information was provided on the system usedor they simply did not know (hence it was not possible for the transcriber of the study to answer this question).

The transcribers were asked to identify which of the CICES classes (version 4.3, Haines-Young and Potschin 2013) were covered by the study, so that the online method finder could make the link between specific methods and ecosystem service types. All 47 CICES ecosystem services are covered in the database. While the CICES version 4.3 does not officially include the abiotic services, for the benefit of completeness, we provided the transcribers with ways of including them. This also makes it possible for future studies which use CICES (version 5.1, Haines-Young and Potschin 2018) to be included (Fig. 11).

We also asked if the method described was used for the demand or supply side of the ecosystem service investigation; 433 examples link a method to the supply side, 303 examples reflected on both – the supply and demand side - whereas so far only 83 described the demand (or actual use) of the ecosystem services. This again might simply be a reflection of development in the ecosystem service research and its available publication. The studies of the earlier years all concentrated on the supply side, where more recent work tended to look at the demand side.

Policy and business applications

As the aim of ESMERALDA is to support the MAES initiative, we were also interested to see if studies considered questions relevant to the policy and business sectors (Fig. 12). While 24 examples consider both, it was interesting to note that over 200 examples mainly had policy questions in mind.

Based on the questions in the database and the questions collected within ESMERALDA and the MAES process, we made a classification to enable users to easily find relevant information for different policy questions (Maes et al. 2018. For policy questions, we classified the cases based on the relevant policy domain and the objective of the policy question. The business questions were classified according to the objective of the question (Table 2).

The development of the database on ecosystem service mapping and assessment applications was a key element running through the entire lifetime of the ESMERALDA project, including all workshops. The process of developing the database created much debate and forced us to be clear about terminology which helped expand the project glossary (Potschin-Young et al. 2018). It also enabled us to develop the method classification by building on work in OpenNESS and OPERA (Potschin-Young et al. 2018)

One aspect to be noted is that, although the database reflects what has been done in the ecosystem service community, it does not include any prioritisation nor recommendations. While a method may have been used many times to analyse a certain issue, no expert opinion is included in the database to help the user decide if this is right or wrong. The number times a method was used does not reflect any indication that it is best; it is just a matter of how many people wrote about it. It is also important to note that entries can reflect ideas that are currently in fashion. For example, although participatory GIS was in vogue for a while, this does not mean that this is the perfect method or that others could not be used to establish a value for a service or to aid prioritisation.

As usual with the creation of reviews such as these, a common understanding of the information asked is needed to avoid different answers to the same question. This was done here through several quality assurance methods within the consortium. However, it needs to be noted that, so far, the database is an ESMERALDA internal product and its usefulness has yet to be reviewed outside the consortium.

Based on the work described here, the following can be concluded:

• A detailed list of methods that have been used in different studies in Europe can help in the implementation of Action 5 of the EU Biodiversity Strategy.
• Methods need to be classified in relation to a set of individual variables (i.e. study dimension, scales, ecosystems or ecosystem services) in order to be appliedto other applications.
• It is important to identify how methods are being used in scientific and policy environments in order to help identify knowledge gaps and provide guidance.
• The presentation of these results provides a base line for Member States to stimulate the process of developing the flexible methodology for mapping and assessment activities.
• One advantage of this practical classification of methods is that it shows that it is possible to capture the different perceptions of ecosystems and their services, according to specific use or non-use of that ecosystem/service. However, as this brings also a level of complexity, a practical guide for selecting methods according to the resources is therefore required.

The authors wish to thank the whole ESMERALDA consortium for their discussion and inputs during workshop in creating the structure and their entries into the database. Special thanks to the additional ESMERALDA Executive Board members for intense debate on structure, expected outcomes etc. Entries are acknowledged in the database through their citation.

This is a product of the H2020 project ESMERALDA and the entire work was funded under EU H2020 research and Innovation programme under grant agreement No. 642007.