Dataset for: A Global Review of Ecosystem Service Trade-offs and Synergies

Methods The dataset is the output of a comprehensive literature-based search that aims to collate all the evidence on where ES relationships have been mentioned and addressed. We applied systematic mapping which is based on the “Guidelines for Systematic Review in Environmental Management” developed by the Centre for Evidence-Based Conservation at Bangor University (Pullin and Stewart 2006). The methodological framework followed the standard stages outlined for systematic mapping in environmental sciences (James et al. 2016). Briefly, we defined the scope and objectives: · We comprehensively review and further explore the global evidence of ES trade-offs and synergies focusing on all systems including terrestrial, freshwater, and marine. · We compiled the evidence on trade-offs and synergies among multiple ES interacting across various ecosystems. · We performed a geographical and temporal trend analysis exploring the distribution of studies across the world examining how the focus on various ecosystem types and ES categories has evolved to highlight gaps and biases. Then we set the criteria for study inclusion (Table 1), searched the evidence, coded and produced the database. Extracted article information including the specific criteria is detailed in Table 1. We searched the ISI Web of Knowledge core collection (http://apps.webofknowledge.com) database, targeting the search on the ecosystem services literature and studies dealing with trade-offs/synergies, win-win outcomes or bundles when managing different ecosystem services in the landscape/seascape. All peer-reviewed journal articles written in English and Spanish have been considered for review. The peer review literature from 2005 to 2021 was reviewed identifying relevant studies according to specific search terms. The relevant search terms and descriptive words derived from (Howe et al. 2014) adding “bundles” and “co-benefits”. Boolean nomenclatures ‘*’ = all letters were allowed after the *, were used on the root of words where several different endings applied (Figure 1). Search terms used were: (“*ecosystem service*” OR “environment* service*” OR “ecosystem* approach*” OR “ecosystem good*” OR “environment* good*”) AND (“*trade-off*” OR “tradeoff*” OR “synerg*” OR “win-win*” OR “bundle*” OR “cost*and benefit*” OR “co-benefit*”) n=5775 Papers were preliminarily coded with a semantic analysis using the R package Bibliometrix (http://www.bibliometrix.org). 1. System Classification: The classification of the dataset into systems, ecosystem services, and country categories was performed as a bibliometric analysis, applying Bibliometrix, an R-tool for comprehensive science mapping analysis. Within Bibliometrix, a list of keywords for each system category (See Table 1 for a detailed list of keywords related to the marine, terrestrial, freshwater, and other systems) was created. The bibliometric dataset scanned these keywords in fields such as titles, abstracts, and keywords. A new field in the dataset was created to assign a system category based on the occurrence of these keywords. If multiple categories' keywords were found, or if no keywords were found, a separate classification (such as "Other") would be assigned. The classification is exclusive; each record is assigned only one system category or "Other" (Mazor et al. 2018). Articles were classified based on the occurrence of the most frequent system words in their title, keywords, and abstract (Mazor et al. 2018). The set of system-specific words was determined by extracting the 250 most frequently used keywords from all considered articles and assigning each word to either system (articles could fall into just one of the four categories). Using this technique, we managed to classify 100% of the papers. 25% of the papers were randomly selected and reviewed to confirm the accuracy of the method that was able to correctly classify more than 95% of the papers. 2. Ecosystem Services Classification: A detailed lists of keywords related to each ecosystem service category (Supporting, Provisioning, Cultural, Regulating) was developed (see Table 1). Applying this technique, we also classified the papers into four ES categories: habitat (supporting biodiversity related), provisioning, regulating, and cultural services (De Groot et al. 2010; MEA 2005; Sukhdev 2010; Wallace 2007). For the classification into ES categories, articles could fall into one or more of the four categories (see Table 1 the keywords used to classify ES). Applying this technique, we excluded 2149 papers that weren’t classified in any of the ecosystem service categories resulting in 3629 papers (see Figure 1). 25% of the papers were randomly selected and reviewed to confirm the accuracy of the method that was able to correctly classify more than 90% of the papers. 3. Country Classification: With the classification of studies in ES categories and the types of ecosystems, the papers were coded according to the country where the study was performed. For country classification using Bibliometrix, the procedure would involve mapping each record to a country based on data fields containing country information (see Table 1 for country names and continents). It was possible to assign a specific country to 2985 studies, removing 644 studies that did not specify the country of study. Of these 2985 papers classified, a proportion were global studies that consider several countries under study (550 global studies). 25% of the papers were randomly selected and reviewed to confirm the accuracy of the method that was able to correctly classify more than 92% of the papers. 4. Critical Appraisal Each publication in this review was critically appraised to make sure it answered the research objectives. Our review contributes to advancing current knowledge by systematically synthesizing evidence on relationships among various ES across these diverse systems. Four criteria, which we adopted from Belcher et al. (2016), were included in our critical appraisal: (1) relevance to the review topic, (2) clarity and logic of how information was obtained, (3) significance of the contribution (does it present any novel concepts, new ideas or theoretical frameworks?), and (4) generalizability (is the context described; do the concepts applicable in other contexts?). Every criterion was scored ranging from 0 to 1, and the sum score obtained from all criteria combined was a useful indicator of the overall quality of the paper and how well the article met the review's goals overall. This analysis offers a quantitative foundation for identifying areas of strength and potential for improvement, further elucidating the different quality and focus of research within the ES trade-offs research. References Belcher, B. M., Rasmussen, K. E., Kemshaw, M. R., & Zornes, D. A. (2016). Defining and assessing research quality in a transdisciplinary context. Research Evaluation, 25(1), 1-17. De Groot, R. S., Alkemade, R., Braat, L., Hein, L., & Willemen, L. (2010). Challenges in integrating the concept of ecosystem services and values in landscape planning, management, and decision-making. Ecological Complexity, 7, 260-272. Howe, C., Suich, H., Vira, B., Mace, G.M., 2014. Creating win-wins from trade-offs? Ecosystem services for human well-being: A meta-analysis of ecosystem service trade-offs and synergies in the real world. Global Environmental Change 28, 263-275. Mazor, T.A.-O., Doropoulos, C.A.-O., Schwarzmueller, F.A.-O., Gladish, D.A.-O.X., Kumaran, N.A.-O., Merkel, K.A.-O.X., Di Marco, M., Gagic, V.A.-O. (2018). Global mismatch of policy and research on drivers of biodiversity loss. Nature Ecology & Evolution 2, 1071-1074. Millennium Ecosystem Assessment (MEA).(2005). Ecosystems and Human Well-Being: Synthesis. Island Press, Washington DC. Pullin, A. S., & Stewart, G. B. (2006). Guidelines for systematic review in conservation and environmental management. Conservation biology, 20(6), 1647-1656. Sukhdev, P. (2010). The economics of ecosystems & biodiversity: mainstreaming the economics of nature: a synthesis of the approach, conclusions, and recommendations of TEEB. UNEP. Wallace K.J. (2007). Classification of ecosystem services: Problems and solutions. Biological Conservation 139, 235-246. Dataset Complete database of the 3629 studies reviewed in this synthesis coded by: N Number of papers AU Authors TI Title SO Publication name JI Scientific Journal AB Abstract DE Authors’ Keywords ID Keywords associated by ISI database LA Language DT Document Type (article, review, editorial, book chapter, letter, meeting abstract) TC Times Cited PY Publication Year SC Subject Categories WC Web of Science categories System Freshwater, terrestrial, marine, and other Habitat Habitat ES category Regulating Regulating ES category Cultural Cultural ES category Provisionning Provisionning ES category Country_Classification Country of study Continent Continent of study Synergies_Trade-offs The term trade-off involves losing one quality or aspect of something in return for gaining another quality or aspect. Synergy is a situation where the use of one ES directly increases the benefits supplied by another ES or a win-win situation Stakeholder_Participation The study interacts with stakeholders at any moment of the study or policy decisions. Critical_Appraisal Articles are appraised to ensure that they are adequate for answering the research question Relevance Relevance to the review question (0 no relevance, 1 relevance) Clarity_and_Logic Clarity and logic of how information in the paper was generated Significance Significance of the contribution (are new ideas offered?) Generalizability Is the context specified, and do the ideas apply in other contexts? Total_Score The sum total score across all critical appraisal criteria