• Walther F, Barton DN, Schwaab J, Kato Huerta J, Immerzeel B, Adamescu M, Andersen E, Arámbula Coyote MV, Arany I, Balzan M, Bruggeman A, Carvalho-Santos C, Cazacu C, Geneletti D, Giuca R, Inácio M, Lagabrielle E, Lange S, Le Clec'h S, Lim ZYV, Mörtberg U, Nedkov S, Portela AP, Porucznik A, Racoviceanu T, Rendón P, Ribeiro D, Seguin J, Šmid Hribar M, Stoycheva V, Vejre H, Zoumides C, Grêt-Regamey A (2025) Uncertainties in ecosystem services assessments and their implications for decision support – a semi-systematic literature review. Ecosystem Services 73: 101714.

• Nicholson Thomas I, Bernado F, Cazacu C, Černecký J, Cortinovis C, Czúcz B, Duchkova H, Kičić M, Lange S, Lecomte X, Lim ZYV, Lotan A, Mörtberg U, Parretta C, Rendón P, Roche P, Tanács E, Vuletić D, Zoumides C, Grêt-Regamey A (Under review) Towards a standardised monitoring of ecosystem condition: a review on indicators and their data sources. Ecological Indicators: Manuscript Number ECOLIND-46889.

• Nicholson Thomas I, Roche P, Grêt-Regamey A (2024) Harnessing artificial intelligence for efficient systematic reviews: A case study in ecosystem condition indicators. Ecological Informatics: 102819.

• Seguin J, Nicholson Thomas I, Rendón P, Cortinovis C, Arany I, Burkhard B, Czúcz B, Duchková H, Geneletti D, Grondard N, Guisado Goñi V, Inácio M, Kato-Huerta J, Kokkoris IP, Le Clec’h S, Lupa P, Mansoldo MDC, Pereira P, Ribeiro D, Šmid Hribar M, Stępniewska M, Tichopádová E, van ‘t Hoff V, Vincente J, Zwierzchowska I, Lange S (in preparation) Linking ecosystem condition and services indicators: a systematic literature review.

In recent years, the importance of healthy ecosystems and the concept of ecosystem services has increasingly gained attention in academia and various decision-making contexts (Burkhard and Maes 2017, Costanza et al. 2017, IPBES et al. 2019, Maes et al. 2020). Ecosystem Services (ES) refer to the multitude of benefits that humans derive from natural ecosystems, encompassing provisioning, regulating and cultural ES (MA (Millennium Ecosystem Assessment) 2005, Burkhard et al. 2012, Maes et al. 2020). ES are critical for human well-being and economic prosperity and understanding them is vital for addressing global challenges such as climate change, land degradation and urbanisation (IPBES et al. 2019). A closely connected approach is the assessment of Ecosystem Condition (EC), which involves evaluating the quality, state or health of an ecosystem. This is crucial for understanding how ecosystems are changing over time and how those changes impact the capacity of an ecosystem to yield ES (Potschin-Young et al. 2018, Rendon et al. 2019, Vallecillo 2022). The latest developments in EC and ES assessment and valuation converge in Ecosystem Accounting, a coherent and integrated approach to measure ecosystem assets, EC and the flows of ES into human activity, which is gathered and presented in a comprehensive statistical framework provided by the System of Environmental Economic Accounts (SEEA) Ecosystem Accounting (Maes et al. 2018, United Nations et al. 2021). Considering EC, ES and Ecosystem Accounting (EA) together provides a holistic approach to understanding and managing ecosystems and offers a robust framework to guide effective and sustainable ecosystem management. By integrating EC and ES assessments and their outcomes into policy and management cycles, stakeholders can make better informed decisions promoting sustainable practices that enhance ecological resilience and human welfare at the same time.

The EU Horizon Research and Innovation Action “Science for Evidence-based and sustainabLe decIsions about NAtural capital” (SELINA*1) aims to provide robust information and guidance that can be harnessed by different stakeholder groups to support transformative change in the EU, to halt biodiversity decline, to support ecosystem restoration and to secure the sustainable supply and use of essential ES in the EU by 2030. As recent literature reviews showed that the documentation of uptake and the uptake itself of the assessment of ES findings in decision-making remains limited (Barton et al. 2022, Termansen et al. 2022), one motivation is to improve the assessment design and communication of results tailored to stakeholder needs in order to increase the uptake in decision-making. The project builds upon the Mapping and Assessment of Ecosystems and their Services (MAES) initiative that, in the context of the EU Biodiversity Strategy 2020, has provided the conceptual, methodological, data and knowledge base for comprehensive assessments on different spatial scales, including the EU-wide assessment (Maes et al. 2020) and assessments in EU Member States*3(i.a. Burkhard et al. (2018)).

Knowledge and data for different ecosystem types in various conditions supplying ES are increasingly available. The growing body of literature is driven by increasing concerns over environmental degradation and biodiversity loss, prompting a need to understand how natural ecosystems contribute to human well-being and how these contributions can be sustained. Within the SELINA project, a significant effort has been dedicated to conducting three large systematic literature reviews aimed at achieving different objectives:

1. derive a minimum set of key ecosystem condition indicators per ecosystem type (Nicholson Thomas et al. 2024, Nicolson Thomas et al. In press);
2. reveal how uncertainties in ES assessments relate to the likelihood of uptake of ES in decision-making (Walther 2025);
3. identifying indicators integrating information on ecosystem condition and services (Seguin et al. In press).

To ensure consistency in terminology and understanding and to base all reviews on the same set of scientific literature, a collaborative effort between SELINA project Task leads was initiated to establish a so-called "Super-Query". Unlike common large queries, which are often tailored to specific research questions, the Super-Query was designed to be a broad, yet precisely structured search strategy that serves multiple systematic reviews simultaneously. It ensures that all three review tasks listed above draw from a harmonized and comprehensive dataset. Thus, this comprehensive search query was designed to harvest a common paper population from relevant scientific literature databases encompassing a wide range of topics that are relevant to the respective SELINA review tasks. Each of the individual literature reviews will deploy their own focused, more specific research query on the here-identified population of papers. The development of the SELINA Super-Query was a pivotal achievement within the project and involved a collaborative effort amongst various researchers from the SELINA consortium. The common underlying query plays a crucial role in supporting the comprehensive literature reviews for the three distinct research objectives building upon it. Furthermore, it aims to gather the current state of knowledge for the time period 2018 - 2022 on ecosystem condition (indicators), ecosystem services, their integration as well as their application in an ecosystem accounting in order to enable the identification of gaps and challenges in the field and to propose future directions for research and policy development.

In order to create a common meta-database of most recent, potentially relevant ES and Ecosystem Condition (EC) studies, as well as applications in the ecosystem accounting context, the task force needed to agree on a unified query approach. Therefore, a series of methodological steps was carried out that were based on a slightly modified PRISMA protocol (Moher et al. 2015).

1. Creation of a task force;
2. Definition of the scope of the search query;
3. Identification of key concepts, pertinent keywords and synonyms;
4. Development of the query string;
5. Fine-tuning and testing the query;
6. Running and recording of the final query to ensure transparency and reproducibility;
7. Processing, organisation and management of harvested literature items to create a final literature database as well as supporting material.

Step 1: Creation of a task force

Step 2: Definition of the scope of the search query

The task force decided to develop a comprehensive search query as a common foundation for the three individual review tasks. As an overarching search query, it was referred to as the SELINA 'Super-Query' (Fig. 1). It was agreed that the SELINA Super-Query was applied to two prominent scientific literature databases, Web of Science and Scopus, both of which offer extensive coverage in the field (Pranckutė 2021). To ensure the inclusion of the latest and most pertinent peer-reviewed literature, the search query spanned the time period from 2018 to 2022, covering the entire five-year period. This update aimed to capture the most recent developments in this scientific field since the conclusion of the preceded ESMERALDA EU Horizon 2020 project*2(2015-2018; Burkhard et al. (2018)). The query was tailored to select English-language literature items only.

Figure 1.

The Super-Query forms a common ground for individual review tasks in the SELINA project. The green shapes outline the collaboration of three work packages (boxes) with their different review tasks (circles), while the blue shapes display the Super-Query as common ground (circle) that ultimately feeds into the common database (box).

It is essential to emphasise that the development of an effective search query is an iterative process. Throughout the series of online meetings, the query underwent multiple rounds of refinements, which were informed by the collaborative input of the team and their impact on the quality and quantity of the retrieved results. The extensive co-creation sessions were conducted to ensure that the search query would meet the unique requirements of each review task while maintaining consistency across the board.

Step 3: Identification of key concepts, pertinent keywords and synonyms

Step 4: Development of the query string

Step 5: Fine-tuning and testing the query

After having identified all relevant keywords, search terms, wildcards and truncations, the fine-tuning of the search query was further optimised to enhance the precision of the query. This process involved modifying the grouping of synonyms, the Boolean operators used to connect them and applying the search filters to different database fields to be queried. For the latter, we varied between: (1) title (TI); (2) title, author and keywords (TI OR AK); or (3) topic (TS) additionally including the abstract (see query below). While skimming through the entries, it was noticed that many papers used the above-mentioned concepts in their keywords without properly addressing them in terms of content, for example conducting an ecosystem service assessment. As the search terms for the general ES and EC concepts initially yielded an excessive number of results (Fig. 2), additional restrictive terms were introduced to enhance specificity (Table 1 Column E and H, Suppl. material 1). The restrictive terms for ecosystem services relate to methods (Barton et al. (2022), MAES Methods Explorer*4), whereas the restrictive terms for ecosystem condition relate to specific measurement and evaluation keywords. For example, only querying #5 with terms related to ecosystem condition resulted in more than 1 million entries, while adding the restrictive terms #6, aimed at making sure that the paper addresses a 'proper' EC assessment and not just drops the term, reduced the number of entries to one tenth. Several loops of testing, refinement, discussion and agreement within the task force helped to iteratively adjust and improve the Super-Query, focusing on balancing inclusivity and relevance by evaluating the quantity and composition of retrieved results.

Figure 2.

Excerpt from the joint work and decision-making process on the selection of most useful search terms. The diagram shows expected proportions of literature items for different parts of the search query. For general ES and EC terms (dashed boxes), it was decided to add restrictive terms to narrow down the results.

The final search string was composed of six search units: (#1) ES/NCPs, (#2) ES synonyms, (#3) ES restrictions, (#4) ecosystem accounting, (#5) EC and (#6) EC restrictions. All six units were connected using the Boolean operator AND. The terms within each unit were generally connected using OR. In unit #2, the NEAR/10 connection was applied to connect the synonyms for 'ecosystem' (Part A) to analogies for 'services' from Part B (Table 1). In unit #5, the NEAR/10 connection was applied to connect 'ecosystem types' from Part A to analogies of 'condition' from Part B (see Table 1)

Step 6: Running and recording of the final query

Step 7: Processing, organisation and management

Here, we provide the final search query using the Web of Science syntax. This query can be typed into the Advanced Search function; the language needs to be set to 'English' and the Publication Years need to be set to 2018 - 2022. On 27.01.2023, 83,950 entries were obtained. The Scopus syntax can be found in Suppl. material 3. On 27.01.2023, it originally yielded 98,574 entries.

(((TI=("ecosystem* service*" OR "nature's contribution* to people" OR "regulat* service*" OR "cultural service*" OR "provisioning service*") OR AK=("ecosystem* service*" OR "nature's contribution* to people" OR "regulat* service*" OR "cultural service*" OR "provisioning service*")) OR (TI=(("ecosystem*" OR "landscape*" OR "ecolog*" OR "environment*" OR "biologic*" OR "habitat*" OR "natur*") NEAR/10 ("service*" OR "disservice*" OR "dis-service*" OR "valu*" OR "benefit*" OR "capacit*" OR "function*" OR "disbenefit*")) OR AK=(("ecosystem*" OR "landscape*" OR "ecolog*" OR "environment*" OR "biologic*" OR "habitat*" OR "natur*") AND ("service*" OR "disservice*" OR "dis-service*" OR "valu*" OR "benefit*" OR "capacit*" OR "function*" OR "disbenefit*")))) AND (TS=(Valuation OR WTP OR "willingness to pay" OR "willingness to accept" OR WTA OR "preference assessment" OR "preference*" OR "benefit transfer*" OR "value transfer*" OR "non-monetary valuation" OR "monetary valuation" OR "elicitation method*" OR "value elicitation" OR PA-BAT OR "Trade-offs" OR "discourse analysis" OR "stakeholder workshop*" OR "interview*" OR "questionnaire*" OR "mental model*" OR "focus group*" OR "concept mapping" OR "Q methodology" OR "Q-methodology" OR "Q study" OR "Q-study" OR "bayesian belief network*" OR BN OR BBN OR "participatory GIS" OR "PPGIS" OR "PGIS" OR "narrative method*" OR "narrative approach*" OR ARIES OR "InVEST model*" OR "biophysical model*" OR "bio-physical model*" OR "biophysical valu*" OR "bio-physical valu*" OR "global environmental flow" OR Mapnat OR "MARXAN" OR "MEB" OR "Ecosystem service map*" OR "ES map*" OR "Ecological importance" OR "Spatial proxy model*" OR ESTIMAP OR GISCAME OR "Cultural Health Index" OR "Environmental importance" OR "POLYSCAPE" OR "ecosystem service quantification" OR "ES quantification" OR "ecosystem service modeling" OR "ES modeling" OR "service providing unit" OR "ecosystem service supply" OR "ES supply" OR "ecosystem service delivery" OR "ES delivery" OR "species richness" OR "biodiversity index" OR "species diversity" OR "ecosystem accounting" OR "contingent valuation" OR "choice experiment*" OR "conjoint analysis" OR "random utility" OR "RUM" OR "Marginal Utility" OR "Lancasters Characteristics demand theory" OR "Marginal rate of substitution" OR "choice model" OR "stated preferences" OR "deliberative valuation" OR "role playing game*" OR "social assessment for protected areas" OR "socio-cultural valuation" OR "expert * elicitation" OR "Afrocentric metho*" OR "Biocultural Methods" OR SAPA OR "participatory mapping" OR "social importance" OR "socio-economic importance" OR "socio-cultural importance" OR "social preferences" OR "Hypothetical policy scenario" OR "Willingness to pay" OR "Willingness to accept" OR "Compensation" OR " Nonmarket valuation survey" OR "Individual welfare change" OR "Equivalent variation of welfare" OR "Compensatory variation of welfare" OR "Multiattribute model*" OR "multi-attribute model" OR "Discrete choice modelling" OR " Final mixture model" OR "Latent Class Model" OR "LCM" OR "Random Parameter Logit Model" OR RPLM OR "Mixed Logit Model" OR " alternative specific conditional logit" OR "hedonic" OR "travel cost" OR "cost-based" OR "cost-effectiveness" OR "production function" OR "shadow pric*" OR "Health valuation" OR "Photo Elicitation" OR "Photo-Elicitation" OR "replacement cost*" OR "averting behavior" OR "economic importance" OR "livelihood assess*" OR "market price*" OR "market valu*" OR "time use" OR "mitigating cost*" OR "preventive expenditure*" OR "cost of illness" OR "participant observation" OR "observe behavior" OR "observe practice*" OR "ritua*" OR "ceremon*" OR "cost-benefit" OR "cost benefit" OR "benefit cost" OR "benefit-cost" OR "MCA" OR "multicriteria analysis" OR "MCDA" OR "multicriteria decision analysis" OR "integrated valuation" OR "deliberative decision making" OR "business accounting" OR "corporate accounting" OR "profit and loss account*" OR ESG OR "Consensus analysis" OR "Natural Capital Accounting" OR "SolVES" OR "inclusive valuation" OR "integrated model*" OR "participatory decision*" OR "Deliberative integration" OR "Alternative cost* method*" OR "Conceptual model*" OR "Corporate Ecosystem Service* Review*" OR "Damage cost* avoided" OR "Defensive expenditure*" OR "Deliberative assessment*" OR "earth observation*" OR "Ecological Connectivity model*" OR "Ecosystem Service* Account*" OR "Ecosystem service* assessment*" OR "Ecosystem service* card game*" OR "Field Observation*" OR "Geo-tagged photo-series analysis" OR "habitat model*" OR "Input-Output analysis" OR "Integrated modelling framework*" OR "landscape function model*" OR "Macro-ecological model*" OR "Narrative assessment*" OR "Net factor income" OR "Opportunity cost*" OR "Participatory scenario planning" OR "participatory valuation*" OR "Phenomenological model*" OR "Process-based model*" OR "Public pric*" OR "Remote sensing" OR "residual value* method*" OR "Restoration cost*" OR "Social Cost* of Carbon" OR "socio-economic data" OR "State and transition model*" OR "statistical data" OR "Statistical model*" OR "survey*" OR "Trait-based model*"))) OR (TI=("ecosystem* account*" OR "natural capital" OR "SEEA EA" OR "SEEA-EEA" OR "SEEA-EA" OR "SEEA EEA" OR "SEEA-(E)EA" OR "SEEA (E)EA") OR AK=("ecosystem* account*" OR "natural capital" OR "SEEA EA" OR "SEEA-EEA" OR "SEEA-EA" OR "SEEA EEA" OR "SEEA-(E)EA" OR "SEEA (E)EA")) OR ((TI=((("ecosystem*" OR "ecologic*" OR "environment*" OR "biologic*" OR "conservation" OR "habitat*" OR "urban*" OR "agroecosystem*" OR "crop*" OR "agricultur*" OR "grassland*" OR "woodland*" OR "forest*" OR "heathland*" OR "shrub*" OR "wetland*" OR "sparsely vegetated" OR "freshwater*" OR "river*" OR "lake*" OR "transitional water*" OR "marine" OR "coast*" OR "ocean*") NEAR/10 ("condition*" OR "state*" OR "status" OR "health" OR "integrity" OR "function*" OR "qualit*" OR "resilien*" OR "capacit*" OR "conservation" OR "naturalness" OR "wilderness" OR "wildness")) OR ("hemeroby")) OR AK=((("ecosystem*" OR "ecologic*" OR "environment*" OR "biologic*" OR "conservation" OR "habitat*" OR "urban*" OR "agroecosystem*" OR "crop*" OR "agricultur*" OR "grassland*" OR "woodland*" OR "forest*" OR "heathland*" OR "shrub*" OR "wetland*" OR "sparsely vegetated" OR "freshwater*" OR "river*" OR "lake*" OR "transitional water*" OR "marine" OR "coast*" OR "ocean*") AND ("condition*" OR "state*" OR "status" OR "health" OR "integrity" OR "function*" OR "qualit*" OR "resilien*" OR "capacit*" OR "conservation" OR "naturalness" OR "wilderness" OR "wildness")) OR ("hemeroby"))) AND (TS=("assess*" OR "map*" OR "valuation" OR "quantif*" OR "value*" OR "account*" OR "indicator*" OR "index*" OR "variable*" OR "indices")))

The database contains the results of the systematic literature review carried out on 27.01.2023 in the Web of Science and Scopus databases. It can be accessed via the Zenodo repository*8. The file contains 108,064 literature entries and is structured through 15 columns ("X", "type", "author", "title", "year", "journal", "volume", "pages", "doi", "abstract", "author_keywords", "indexed_keywords_scopus", "keywords_plus_WoS", "n_duplicates", "origin"). Explanations on the structure can be found in Suppl. material 4.

Language

License

Repository name and location

The profound collaboration of review task leads in this early phase of the SELINA project led to the successful compilation of the operational SELINA Super-Query database. This comprehensive database, containing 108,064 entries, is a fundamental resource for the succeeding literature reviews in the project. It forms the basis for ensuring consistency in the selection of research publications and will support the achievement of specific objectives within each review task. Review task leads will continue to use the SELINA Super-Query database to sub-query relevant literature and proceed with their specific review objectives. Furthermore, the agreement on a consistent terminology laid an important foundation for further collaboration within the SELINA project. The co-creation process and collaborative efforts within the project consortium have been instrumental in creating a valuable resource to be used by the project and beyond.

Funded by the European Union under grant agreement No. 101060415, SELINA (Science for Evidence-based and sustainabLe decIsions about NAtural capital).

The first two authors should be regarded as joint first authors.