literature review on ecosystem services

• Open access
• Published: 23 July 2020

A global view of regulatory ecosystem services: existed knowledge, trends, and research gaps

• Wondimagegn Mengist 1 , 2 ,
• Teshome Soromessa 2 &
• Gudina Legese Feyisa 2  

Ecological Processes volume  9 , Article number:  40 ( 2020 ) Cite this article

18k Accesses

36 Citations

4 Altmetric

Metrics details

Ecosystem services (ES) are growing fields of research. It helps to provide an inherent way to understand the synergy and trade-offs between human beings and their natural environment. Regulatory ecosystem services (RES) are significantly important to maintaining the world in which people can live, and control the negative effects of flood, disasters, and diseases. It can also provide regulatory services like ecosystem protection, human safety, and the provision of other ES. However, emerging ES decision-making agendas focus on ES that is tangible and has a direct link with human well-being. Thus, the attention given to RES is low due to its less tangible benefits and complexity to measure the benefits. Disregarding and lack of attention from policymakers and scientific community may lead to unintended risks to human well-being and significant influences on the provision of other ES. This study describes the research trends on RES, knowledge generated, and the major limitation. We concluded that though there is an exponential growth of scientific publications on ES, no adequate studies were found on RES. Also, the existed studies varied in their size and types of RES indicators covered, habitats/ecosystems, and geographic extent addressed. There was also a lack of connecting knowledge generated on the benefits of RES with the national policy of natural resource management, inconsistency of ES classification, and methodological diversity. Therefore, scientific communities are promoted to link RES studies with human health. Besides, the researcher should give priority for the least studied ecosystems and its services, developing robust methodology, and proposing management options to enhance the regulatory services of ecosystems.

Introduction

Ecosystem services (ES) are all the benefits which human can derive from the natural ecosystems for their physical, social, and economic well-being (Costanza et al. 1997 ; Daily 1997 ; MA 2005 ). Currently, the term ES is popular in contemporary scientific research and policy agenda (Braat and de Groot 2012 ; Fisher et al. 2009 ; Seppelt et al. 2011 ). This is because ES is highly valuable (Costanza et al. 1997 ) and beneficial to families, communities, and economies (Boyd and Banzhaf 2007 ) and helps to maintain the conditions of life on earth (Deal et al. 2012 ). Healthy functioning ecosystems have wide-ranging importance for human health by providing benefits like food, building materials, medicines, climate regulation, disease prevention, provision of clean air, water, soils, and landscape for cultural services and spiritual purpose (Daily 1997 ; Deal et al. 2012 ; MA 2005 ; Vo et al. 2012 ).

Over the years, several typologies have emerged to categorize ES. These were frameworks developed by Millennium Ecosystem Assessment (MA 2005 ), The Economics of Ecosystems and Biodiversity, and The Common International Classification of Ecosystem Services (CICES) in 2010 (Haines-Young and Potschin 2011 ). Therefore, we prefer to use MA framework to structure our study analysis, because the framework is flexible and the most commonly used approach to evaluate ES in this study and others (e.g., Liquete et al. 2013 ; Mengist et al. 2019a ; Talbot et al. 2018 ; Weitzman 2019 ). Based on the ES framework developed by MA in 2005, the variety of ES benefits to humans can be grouped into four classes: provisioning, regulating, cultural, and supporting services. Regulating ecosystem services (RES) are defined as “the benefits obtained from the regulation of ecosystem processes” (MA 2005 ). It comprises the various ways whereby the ecosystems regulate the natural environments. It helps to reduce the impacts and effects emanated from both natural and anthropogenic activities that cause risk to human health and ecosystem quality. RES, therefore, protect the natural environment using mechanisms like water purification and waste treatment, air quality maintenance, soil erosion control, flood protection, climate regulation, pest and disease regulation, pollination, and regulation of frequency and intensity of natural hazards’ flow (Kandziora et al. 2013 ; MA 2005 ; Smith et al. 2013 ; Sutherland et al. 2018 ; Villamagna et al. 2013 ). Further, RES has a significant effect on the provisioning capacity of other ES (Boyd and Banzhaf 2007 ).

RES is grouped either in the final ES like climate regulation and natural hazard or in a significant leading to final ES such as water quantity and purification. Some other is primary or intermediate ES which includes pollination, disease, and pest regulation (Watson et al. 2011 ). Regulation services of natural hazards, for instance, flood regulation, are determined by the hydrological system (Stürck et al. 2014 ). Climate regulation is a final ES and includes absorbing greenhouse gases, enhancing evapotranspiration for rainfall occurrence, and controlling a surface albedo. This can extend from local to global scale regulatory services and has significant impacts on human well-being (Smith et al. 2013 ). Disease and pest regulation is an intermediate ES, and pollination is a primary or intermediate ES that has direct impacts on human well-being. It has large impacts by affecting the provisioning services like crops, plants, and livestock which are the main sources of food for humans (Watson et al. 2011 ).

Despite those benefits, RES is often less acknowledged and undervalued by people due to their less tangible benefits (Kandziora et al. 2013 ; Sutherland et al. 2018 ). It has difficulties measuring its contribution to human safety because RES provides indirect benefits to human well-being through maintaining the quality of the environment in a real sense which is critical services to the society. These caused RES to be overlooked in decision-making processes because more attention is given to ES that has more evident links with human well-being (Sutherland et al. 2018 ; Villamagna et al. 2013 ). Besides, RES is “process-driven,” and data required to assess and evaluate the services at large scale were unavailable and become a bottleneck to mainstreaming into the policymaking agenda (Villamagna et al. 2013 ). There were also weak efforts to adequately connect regulating services with policymaking and ES assessment frameworks (Sutherland et al. 2018 ).

As a result of those challenges, RES becomes impeded from sufficiently considered in environmental decision-making processes. Thus, according to Sutherland et al. ( 2018 ), the ES management approach that ignores RES may bring “management trade-offs” that cause unsuitable environment for human health and favoring provisioning ES over RES that in turns induced pressure on the ecosystems. These also result in the undervaluing of ES and fail to fully understand the entire environmental and economic trade-offs (Keeler et al. 2012 ).

There were various review works on assessing and evaluating the state of the art of the ES. Just to list some of them: on ecosystem services in general (Seppelt et al. 2011 ), on trends of ES research (McDonough et al. 2017 ), on regulating ecosystem services (Sutherland et al. 2018 ), mapping ES value (Burkhard et al. 2012 ; Martínez-Harms and Balvanera 2012 ), the role of agriculture in ES (Tancoigne et al. 2014 ), economic valuation (Laurans et al. 2013 ), ecosystem services in landscapes (Englund et al. 2017 ), cultural ES (Milcu et al. 2013 ), ES integration with conservation (Egoh et al. 2007 ), with limited geographical areas, i.e., in Latin America (Balvanera et al. 2012 ), and Africa (Wangai et al. 2016 ), a meta-analysis of some key terrestrial regulatory ES (Viglizzo et al. 2016 ), and trends of forest ES (Mengist and Soromessa 2019 ). However, neither of the above studies so far addresses a detailed bibliographic review, spatial distribution, trends of indicator services and ecosystems, and gap on RES studies. Thus, we decided that it is important to provide information on the overall trends of RES research on a global scale. Also, the study can help researchers to identify the least and the most addressed indicators and its ecosystems, the types of challenges that the researchers were encountering, and the gaps that needed further research works.

Since ES provides a variety of benefits to human well-being, having a scientific output on ES can help to motivate policymakers to work towards reversing ecosystems from further degradation. Although human wellbeing is the core issue in ES, the existence of rapid population growth, economic growth, change in human consumption patterns, and climate change adversely affects the ES services. Accordingly, ES assessment is important to broaden the knowledge on ES, to raise the awareness level, and to be an agenda from global to the local level (Alamgir et al. 2014 ; Fagerholm et al. 2016 ). This study, therefore, formulated specific research questions. These were as follows: (1) What is state-of-the-art in RES? (2) Which RES indicator(s) had the highest and the least number of studies? (3) What are the current challenges impairing RES studies? and (4) What are the lessons learned and the way forward for ecosystem studies related to regulatory services?

The aim of the article is to provide an overall picture of trends of RES studies, give a comprehensive evaluation of the approaches used for ES assessment, map the conducted studies, and identify the gaps to be filled by future research works. Therefore, the work helps to define the status quo and deepen the trend analysis using related research papers. To that aim, the review addressed the following specific objectives:

To analyze the state of the research trends on RES and the coverage of that published knowledge

To identify the most and the least studied ecosystems and their regulatory ES indicators

To analyze and highlight the main research gaps and pinpoint the way forward

Methodology

Data sources.

The approach followed the literature search protocol of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (Moher et al. 2010 ). The review cannot be an exhaustive search of the literature, though it covers the largest parts of the related literature on the topic. The study covers limited databases such as Scopus, ScienceDirect, and Google Scholar. To guarantee the accuracy, this work was based on analytical processes from the framework of search (related articles from the identified databases), appraisal (include articles that include RES or regulating services on their title), synthesis (download and read the articles to include publications that cover at least one RES indicator), and analysis (extracting useful data from the included articles) (SALSA), which was applied by most reviews (Grant and Booth 2009 ; Malinauskaite et al. 2019 ; Mengist et al. 2019a ; Perevochtchikova et al. 2019 ). The aim was to reduce the risk related to publication bias and to increase the scientific validity of the review work (Mengist et al. 2019b ).

Before the actual systematic review search, a pilot literature search was done to refine the searching keywords to cover the targeted ES (Howe et al. 2014 ). The articles were peer-reviewed journals from the three data sources, and searches were finalized in April of 2019.

Literature searching terms

The following syntax was used: TITLE-ABS-KEY (“climate regulation” OR “air quality” OR “water regulation” OR “erosion regulation” OR “pest regulation” OR “pollination”) AND TITLE (“regulating ecosystem service” OR “regulating service” OR “regulatory ecosystem services” OR “regulatory services”). As shown in Table 1 , the search terms had run in separate or with limited combinations that considered the requirements, or limitations, of the database used.

Article selection criteria

Article selection followed sequential assessment steps. First, document abstracts were scanned to ensure the papers broadly addressed the following selection criteria, and if the papers did not meet the criteria, the papers were excluded. The literature from the databases was searched based on the following fixed set of inclusion criteria:

The literature should address at least one service from regulatory ecosystem services.

The predefined keywords should exist as a whole at least in the title, keywords, or abstract section of the paper.

The paper should be published in a scientific peer-reviewed journal between 2005 and the cutoff date on April 18 of 2019. This period of time was linked with the work of MA report, and the terms ecosystem and ecosystem services were consistently used.

The paper should be written in the English language. Next, the selected papers were then subjected to further analysis.

Data collection

Basic information was extracted from 46 articles that cover the types of ES studied and their indicators (like climate regulation and erosion control); methods of quantification/mapping, i.e., biophysical or economic terms; and the ecosystem types (forest ecosystem, watershed, agricultural land, and the like). The data were organized on the general characteristics of the articles and on the specific parameters used to value/quantify/map the ES. The general information of the articles includes the year of publication, analysis types (quantitative, qualitative, mapping, or mixed), types of study and scale, numbers of ES assessed, and country/region where the study was conducted, whereas the rest of the publication was used for generating existed knowledge and trends of research on the topic.

Data analysis and presentation

The data from the final list of selected articles were summarized to identify and qualitatively assess the current knowledge on RES, spatial scale and ecosystems, type of assessments used, and gaps observed. The systematic review also captures the state of the research for policy implication and implementation and the kinds of scientific research needed in the future from various disciplines that have interest and capability to conduct research.

Research trends in ecosystem service

The literature search result depicts that recently, there were enormous scientific publications on the field of ES on diverse ecosystem types. Until the publication of articles on ES, for instance, Costanza et al. ( 1997 ) and Daily ( 1997 ), the concept and application of ES in the scientific sphere were limited (Weitzman 2019 ). Since 2010, the number of publications had increased exponentially though few publications on ES existed before 2010. This is a common trend in ES research, and the possible reason would be emerging of specific journals on ES in the mid-2000s and the existence of seminar and workshop at international level on ES (Costanza et al. 2017 ; Liquete et al. 2013 ; Mengist and Soromessa 2019 ). Mainly after the publication of the MA report in 2005, the scientific community was inspired to conduct studies on the various benefits of ecosystems for human well-being. This indicates the existence of an academic interest in ES studies so as to inform policymakers to design strategies to use ecosystems sustainably. Relatively, the publication size on RES was not large, for example, publications indexed in the Scopus database that addressed RES were eight in 2005 and reached 100 in 2018 (Fig. 1 ).

The number of papers published annually from 2005 to April 2019. a Publication trends on ES. b Publication trends on regulatory ecosystem services

RES indicators and spatial distribution of the selected studies

Compared to the total number of publications indexed in the Scopus database, only some of them contain the phrase “regulating ecosystem services”/“regulating services”/“regulatory ecosystem services” or “regulatory services,” in their title or abstract and keywords. Beyond that, only a few of them focus on the quantification/mapping/valuing of one or more RES indicators, and the majority of works were general assessments. Results were generally given as the absolute number from the selected case studies, followed by the percentage share of case studies in parentheses. From the 46 publications sourced for this meta-synthesis, 27 (58.7%) discussed a single RES, eight (17.4%) studied two RES, seven (15.2%) discussed three RES, and four (8.7%) papers included four RES. The majority of the publications merged different indicators of ES with other functional groups like provisioning, cultural, and supporting services.

Figure 2 describes the spatial distribution of regulating ecosystem service studies. The 46 studies were conducted in six continents: in Asia (12 studies), Europe (19 studies), Africa (9 studies), Australia (1 study), North America (4 studies), and South America (1 study). The study represented 26 countries except for the four studies that were conducted at the regional level in Europe that cover more than one country. The selected studies had covered nine, seven, five, and three countries from Europe, Africa, Asia, and America, respectively, and Australia had a single study. This diverse geographic focus and being conducted at various spatial scales suggest an understanding that RES is relevant for ecosystems and human health. The selected case studies covered small areas of the world and were not enough to cover the various indicators of RES. Even though small, the literature on RES has been growing steadily over the last few years. All the selected publications had got published since 2010, and the possible reason might be the subsequent publication of TEEB in 2010, the IPEBS in 2012, and the existence of a seminar on ES at the international level.

The distribution of RES case studies globally based on study location ( N = 46 studies which specified a geographic location). The publications on RES that were published from 2005 to 2019 demonstrate a broad spread across the globe, with a relatively notable concentration of studies in Europe and Africa

There is a diversity of ES classification that causes difficulties and inconvenience in the comparison between different studies (Fletcher et al. 2011 ). Besides, there were difficulties to match the RES indicators used by some studies with the classification of MA ( 2005 ). However, this challenge was overcome, except for the uncategorized service, as follows. As shown in Table 2 , ES such as “flood regulation,” “bird predation of herbivorous insects,” and “cyclone regulation” were grouped under natural hazard regulation. Also, “carbon storage,” “carbon sequestration,” “climate regulation,” “micro-climate regulation,” “temperature,” “thermal comfort of inhabitants,” and “urban heat islands” were categorized under climate regulation in this paper classification. The previous classification by Liquete et al. ( 2013 ) incorporates “weather regulation” as an independent of climate regulation considering their scale, processes, and beneficiaries.

Current knowledge on regulating services

The services mentioned by the selected 46 papers were grouped into those in which the services belong. Based on the indicators of RES, most of the literature addressed climate regulation services that had 25 cases followed by natural hazard regulation, water regulation, and erosion regulation by 12, 10, and 9 cases, respectively. However, none of the studies covers the pollination services of ecosystems (see Fig. 3 ). A study in the USA by Brainard et al. ( 2016 ) assessed the pest regulatory services, and Inkoom et al. ( 2018 ) studied pest and disease regulation services on a terrestrial landmass in Ghana. A study by Bicking et al. ( 2018 ) on a mapping of nutrient regulating ecosystem service by using the nutrient nitrogen is an example in Germany. The study used a local and regional scale study site to infer the conclusion on the spatial scale effect of nutrient RES. The study determined the existence of a regional differentiation on the supply and demands of nutrient regulation.

The number of case studies and RES indicators based on MA 2005 classification. Based on indicators of RES, climate regulation and natural hazards were relatively well studied, whereas the pollination, pest, and disease regulation services were the least studied. Based on the studied ecosystems, urban and forest ecosystems had more case studies compared to sea/marine, wetlands, and grazing lands

From the selected 46 number of literature, the total number of indicators of RES addressed was summed up 75. Multiple RES indicators were taken from a single study when they represent each indicator separately, and according to Brander et al. ( 2013 ), this is one of the peculiar characters which a meta-analysis should control. Except for a single study, the rest of the case studies were categorized into either of the indicators in RES. The uncategorized study was a study by Davies et al. ( 2017 ) in Britain on urban trees. It was a general study and tried to address and identify constraints and drivers to apply the ecosystem service approach to urban forest management by British local authorities. As a result, the study did not address a single indicator from RES to derive a conclusion.

Based on the ecosystem type, the urban ecosystem had 20 number of case studies of which more than half cover climate regulatory services that include urban heat, temperature, microclimate, carbon storage, and sequestration. Climate regulation service was well studied in the urban ecosystem than any other. The next landscape type was the forest that had 15 case studies of which climate regulation and natural hazard regulation services were relatively well addressed (see Fig. 3 and Table 3 ). On the other hand, the less studied ecosystems were sea and marine ecosystems, grazing lands, and wetlands. Such ecosystem site needs scientific studies to evaluate/quantify/map the various regulatory ecosystem services that the ecosystems have had to the well-being of human society. Thus, the result from different categories of RES is underpinning the existence of confusion between priority and sensitivity to human well-being.

The RES studies had various variables of interest (Fig. 4 ), and numerical crosses were made between the scale of the study site and the ecosystem. The classification of study size scale was done by modifying the Martínez-Harms and Balvanera ( 2012 ). It was concluded that 34 (73.9%) of the papers were conducted at local (watershed, river catchment, cities) scale, eight (17.4%) papers at a national level (covering the whole geographic area of a country), and four (8.7%) papers at regional (studies covering the whole continent or more than one country administrative areas) scale. In addition, the total areal extent of the study used for the assessment of RES was a range from small size to a larger size ecosystem area in hectares. For instance, from the selected studies, which clearly defined the total study area covered by their work, the smallest size was 7.2 ha in Turkey at the urban garden site for the assessment of carbon storage and sequestration and runoff retention (Hepcan and Hepcan 2018 ), and the largest area coverage was 139 million hectares of lands in China to study water and climate regulation in alpine grassland ecosystem (Pan et al. 2014 ). This infers that most of regulatory ecosystem service indicators were studied at small-scale areas with the main aim of producing site-specific knowledge and information on the valuing and mapping of the ecosystem types.

The number of studies across scale levels and ecosystems

During the review, the only continent that had studies covering the entire geographic space was Europe with three studies. The first study was on mapping the flood regulation services in Europe to provide spatial analysis on its demand and supply side by Stürck et al. ( 2014 ). The second was a study by Stürck et al. ( 2015 ) on regulating ecosystem services that consider the role of past and future land use change across time and space. They studied the effect of historic land use land cover change on the supply and demand of RES, except Croatia. The third was by Larondelle et al. ( 2014 ) on mapping the diversity of regulating ecosystem services in European cities. The study analyzed the provision of ecosystem services in 301 large urban zones from 27 European countries.

As shown in Fig. 5 , in terms of year of publication, the selected literature includes publication which started in 2011, even if the search was between 2005 and April of 2019. There was no publication included in the final selected papers that cover the period from 2005 to 2010. The smallest number of publications was recorded in 2011, 2012, and 2013, whereas the largest publication number was in 2016 and 2018. In sum, the number of the publication including the term regulating/regulatory ecosystem services in the title of the articles was insignificant.

The number of studies of the selected literature based on study scale and year of publications

Regulatory ES: study approaches and methods

Several distinct types of RES studies can be distinguished. It can be broadly categorized into RES assessments at specific sites using modeling and valuation, review and theoretical papers for conceptual development, and methodological papers for checking approaches, testing, and developing methods. RES studies involve various kinds of methods to quantify values and map the service. The common techniques employed by researchers were either biophysical or integrating biophysical and economic/monetary terms (Fig. 6 ). The biophysical method refers to the value of the ecosystem in tons per hectare estimation, monetary terms like financial benefits and/or costs per hectare and year estimation, and the rest used percentages, scoring, and for the socio-cultural value of ES to society. It was the most common (48%) followed by research works that integrated both biophysical and economic/monetary terms (22%), to quantify either singular or multiple ecosystem services.

Methods of assessments used by the selected publications

In terms of data types, 22 studies (47.8%) used mixed data of primary and secondary sources; thirteen studies (28.3%) and eleven studies (23.9%) used primary and secondary data types, respectively. Thus, less than 30% of the studies derived their results using primary data of field observations or actual measurements, whereas nearly one-fourth based their results on secondary data.

Figure 7 represents the category of the selected published articles based on the purposes of the research conducted. Most of the studies, which constitute 78.3%, were for the generation of site-specific knowledge on various indicators of RES across different landscapes. However, few studies had a research purpose for methodological assessment and development, mainstreaming ecosystem services with policy agenda, and recommending management options to maintain both the quality and quantity of the benefits of the given ecosystem service to human well-being.

Main purposes of the selected published articles

Gaps and difficulties observed in RES studies

The majority of the selected studies, namely 28 papers (60.9%), had not explicitly mentioned the difficulties and limitations in their study. However, they either recommend the need to conduct another study or their study is the first in its kind in the locality. This implies that the concept of ecosystem services research is recent and demands a lot of research work to make it rich in its methodology and models. Based on the challenges and limitation mentioned by the selected published articles, the existence of methodological uncertainties is mentioned by 17.4% (8 papers) which was followed by data and model limitations, which is present and discussed in 10.9% (5 papers) and 8.7% (4 papers) of the selected papers, respectively (Fig. 8 ). According to Grêt-Regamey et al. ( 2013 ), uncertainty in ES valuation and quantification has a significant impact on the amount of the predicted value. For instance, in a study in Landschaft Davos on carbon sequestration, uncertainties caused a change in its total value by 48% (Grêt-Regamey et al. 2013 ).

The most common difficulties mentioned by the selected studies

Spatial distribution and focus area of RES studies

The study result revealed that research on RES has shown more concentration in Europe and Asia which together shared more than two-thirds from the total selected papers. In agreement with another review on ecosystem services, at individual country level, China had shared the largest number of publications and the result was in agreement with the study of Luederitz et al. ( 2015 ), but she ranked next to the USA in Seppelt et al. ( 2011 ) review work. The number might be larger than this if the review work covers publication from the Chinese language. Because China had a journal ( Shengtai Xuebao/Acta Ecologica Sinica ) that published a number of articles on urban ecosystem services (Luederitz et al. 2015 ). A meta-analysis and systematic review work that excluded publications of non-English language may miss important research findings.

Ecosystems provide multiple ES to human beings (Lee and Lautenbach 2016 ). Regardless of the reason behind the abundance of studies on urban and forest ES (Table 3 ), the result indicates that they play an important role in human safety and thus the best available methods attracted researchers. Besides, most of the case studies were conducted spatially at the local level. Similarly, Malinga et al. ( 2015 ) reported that 92% of the studies were conducted at a local scale, and the reason was the availability of secondary data at this scale. Based on RES indicators, climate regulation service was the most investigated topic in several publications. One of the reasons for the existence of large study output on climate regulation service was the establishments of “The Intergovernmental Panel for Climate Change” and “reducing emissions from deforestation and forest degradation in developing countries, and the role of conservation, sustainable management of forests, and enhancement of forest carbon stocks in developing countries” (Goslee et al. 2016 ). These consequently increase the information demands of most governments and many other international organizations (Egoh et al. 2012 ). However, the study untouched the effect of the trade-offs of climatic extremes such as severe drought and global warming impacts that could negatively affect ecosystem functioning and stability. Other ecosystems like wetlands, sea/marine, and grazing land ecosystems had the least attention in the research community though they have had a significant contribution to human well-being. This created unbalanced research works and outputs on the different types of ecosystems and indicators of RES. In addition, the study found out the presence of less care for documenting valuable information in the articles like the geographical extent of the study site for instance (Krkoška Lorencová et al. 2016 ; Li et al. 2018 ; Walz et al. 2019 ) and lack of stating explicitly the difficulties that impact the study findings.

The dominance of site-specific ecosystem assessment was observed. This was mainly applied to evaluate/quantify/map the specific ecosystem types using monetary and/or biophysical terms. On the other hand, the number of publications focusing on policy implication and suggesting methodological options was too small. This might be linked with the development level of the concept and the methodological advancement to measure the ecosystem services to persuade policymaker institutions.

Research gaps and future direction

This review has illustrated the view on RES studies, but more than looking for gaps in RES research, our motive was to find those habitats and indicators for which research should be prioritized. The existing research work thus considered spatial extents ranging from local case studies to regional and global assessments. Results show that research was compelled by divers’ motives like generating site-specific knowledge, methodological development, policy implication, and management options (Fig. 7 ).

Though the difficulties mentioned in the reviewed papers, which are displayed in Fig. 8 , were mainly focused on uncertainties from methodological and data types, we identified additional gaps in RES studies. These gaps may inhibit future progress in RES studies and slowly mainstreaming them into the decision-making process. The identified gaps were grouped into five basic research gaps. First, the literature misses a fair representation of studies from each indicator of RES and ecosystems. The existed studies concentrated on climate regulation, hazard regulation, water, and erosion regulation. There was no sufficient outlook on pollination, pest and disease, air quality regulation, and nutrient regulation services. Mengist and Soromessa ( 2019 ) have noticed in their meta-analysis study that the pollination, pest, and human disease regulation services were the least addressed and received less attention from the scientific community. Among other things, the most common factors would be related to lack of data, challenges in estimating their value, and lack of well-designed methods. In terms of ecosystems, there are no adequate studies on wetlands, grazing lands, and sea/marine ecosystems. These ecosystems need critical studies using biophysical, monetary/socio-economic, and socio-cultural data. Comparatively, an urban ecosystem is widely investigated in scientific works from all indicators except in terms of pest and disease and pollination services. Though the topic is novel, it is unsurprising that most studies examine the general view on the value of the RES. There is a lack of an adequate number of studies that able to assess the various biomes of its regulatory services and/or challenges that affect those potentials.

Second, most studies were site-specific and conducted by multi-disciplinary teams but lack forwarding strategies to link ES into the decision-making process. According to Droste et al. ( 2018 ) and Malinauskaite et al. ( 2019 ), ecosystem service research needs multi-disciplinary collaboration as well as the inclusion of local perspectives by involving local stakeholders. Most of the papers in this review work had a transdisciplinary background and are important to mainstreaming the concept with government policy, though the actual effort was weak. The same concept was mentioned by Weyland et al. ( 2019 ); mainstreaming ecosystem service assessment into policymaking is helpful at the initial stage of the ecosystem service management phase. Besides, the notion of ES is increasingly used for making a decision on natural resource management (Grêt-Regamey et al. 2013 ), and in the long run, the use of ES concept can help to develop policies to bring sustainability on the functioning of ecosystems and its benefits into society (Balvanera et al. 2012 ). Thus, most of the selected RES papers had predominantly discussed the conceptual and theoretical aspects, with only a few exceptions of case studies for instance (Ifatimehin 2014 ; Missall et al. 2015 ; Oka et al. 2019 ) those which address the interaction between human well-being and ecosystem services.

At least the following two possible reasons can be outlined to explain for lack of mainstreaming outputs of RES studies into policymaking agenda: (i) it demands the studies to have detailed and accurate information across various spatio-temporal scale (Caro et al. 2020 ; Englund et al. 2017 ), and (ii) it needs sound result on the socio-ecological interrelationship between society and ecosystems, the ES society gain from the natural habitats, and human influence on the specified habitats (Lautenbach et al. 2019 ).

Third, there is a dearth of uniform methodology and inconsistency in ecosystem service classification. Both biophysical and/or monetary terms can be used in similar indicators and ecosystems, but the challenge was inconsistency in ES classification. This may confirm that gaps remain in the ES classification. Similar to Nemec and Raudsepp-Hearne ( 2013 ) and Englund et al. ( 2017 ), we find the existence of methodological and ES classification diversity on ES research. This may create difficulties to integrate ES assessment results for meta-analysis studies—an issue which is already discussed in CICES itself by Haines-Young and Potschin ( 2011 ) and recently by Englund et al. ( 2017 ). In this context, providing simple and easy-to-use methods, models, tools, and ES classification is fundamental to guarantee a successful integration of knowledge on regulatory services. On the other way, the existence of diverse ways of ES classification confirms that there are many useful ways to classify ecosystem goods and services. These pluralisms of ES classification may be helpful for studies to address different goals (Englund et al. 2017 ).

This is perhaps similar to the findings from Seppelt et al. ( 2011 ) that aimed to quantitatively review of ecosystem service studies and the existence of inconsistent ES classification impacting to categorize in any of the RES indicators. A similar conclusion was formed by Fisher et al. ( 2009 ) that inconsistency of ES classification can cause challenges for making meaningful research results and difficulties to make comparisons and integration of study output with other data (Englund et al. 2017 ). According to Villamagna et al. ( 2013 ), therefore, to improve RES assessments, developing methodology is a prerequisite. In the real term, there is no one-size-fits-all approach to assess ecosystem benefits. It is important to be aware of the limitation of existing ES classification. Thus, choosing the most suitable ES classification that considers the purpose of studies is mandatory (Heink et al. 2016 ; La Notte et al. 2017 ). The type and size of benefits are related to the ecosystems. For instance, a heterogeneous landscape can provide many ES. To reduce the challenge, the application of appropriate methods that examine the data availability, time frame, competence, and others to quantify the capacity, demand, and flow services is essential (Englund et al. 2017 ; Nemec and Raudsepp-Hearne 2013 ).

The fourth challenge is the lack of nearly balanced monetary value estimation per hectare per annum for nearly similar ecosystems. A meta-analysis on the forest ecosystem services valuation methods by Mengist and Soromessa ( 2019 ) also concluded that methodological inconsistency on monetary estimation exists for similar ecosystems across the globe. There was also a challenge related to the existence of a small number of case studies on similar ecosystems and indicators of RES. This can be a research challenge in the future to make systematic analysis and comparison across site and scale, as also emphasized by Malinga et al. ( 2015 ). As a solution, Costanza et al. ( 2017 ) forwarded the scientific community to develop a methodology that helps to map, model, value, and manage ecosystem services and to effectively address the final output to the end-users. Finally, numerous studies found in this review had a small area coverage in hectares. However, their methods were poorly described, lack a detailed description of the data sources, and have no justification for the use of generic data and models at a small-scale level of studies. This might be due to the high cost of resources and time for the primary data collection, as also noticed by Malinga et al. ( 2015 ) and Nemec and Raudsepp-Hearne ( 2013 ). As a result, the researchers have more relied on secondary data sources for ES estimation and assessment. This was supported by the study of Martínez-Harms and Balvanera ( 2012 ) that one of the most common approaches in RES study was the application of secondary data to model ecosystem services.

Therefore, there should be high research outputs with regard to RES across different ecosystems using regulatory ES indicators, because it is not yet possible to fully account the role and benefits of RES to human safety and for other ES provision. Also, there is no adequate size of studies to mainstreaming RES into the policymaking agenda. In parallel, Sutherland et al. ( 2018 ) suggest improving ES assessment frameworks “by including indicators of regulating ES that differentiate between the capacity to provide a regulating ES, the demand for the same, and the actual service that is conveyed.”

Comparison to other ecosystem service review work

The research gaps mentioned in this paper coincided with other review work on ecosystem services. One of the main challenges was the inconsistency in methodology and terminology used by the studies. Englund et al. ( 2017 ) reviewed “How to analyze ecosystem services in landscapes” and claimed that the existence of inconsistency in the use of terminology affects the choice of methods used to value the services. Similarly, Costanza et al. ( 2017 ) and Mengist et al. ( 2019a ) highlighted that ES research had inconsistent approaches to model, assess, and value ES. There was variation in the priority given to RES indicators and ecosystem types which was also reported by Balvanera et al. ( 2012 ) on ecosystem service studies in Latin America. They mentioned that the current ES research work focuses on those having impacts at a global level like carbon and a regional scale (water resources). On the contrary, other ES like disease regulation, coastal protection, pollination, and floods that have local-level importance had got less priority by the scientific communities.

The interdisciplinary nature of ecosystem service work was observed in this systematic review work. The result was also supported by the findings of Malinga et al. ( 2015 ) and Abson et al. ( 2014 ). This was also pinpointed by Droste et al. ( 2018 ) that interdisciplinary research work and multiple perspectives and types of ES values were observed in ES researches. Another common concern, which coincides with the observation of this study, was the lack of forwarding clear strategies in the selected papers to integrate ecosystem services into a national policy of resource management and mainstreaming to other development agenda (Malinauskaite et al. 2019 ; Sutherland et al. 2018 ). However, mainstreaming ES to policymaking and development agenda needs efficient and explicit information both on the status and trends of the ecosystem and its associated benefits (Maes et al. 2012 ).

Limitations of the review

This study attempts to assess the general trends, the types of RES indicators and ecosystems, and the gaps observed in RES studies that were conducted from 2005 to April of 2019 at the global level. The assessment tried to indicate the current state of knowledge in RES and the indicators versus ecosystems that had more focus and the least attention from the scientific community. It is not, however, this systematic review free from limitations. Firstly, the assessment ignores publications that have a concern on RES without including the term regulating ecosystem services in the title of the article. The second limitation was linked to the databases used to search related literature on the issue. Other data sources like the Web of Knowledge were inaccessible to search the archives to broaden the possibility of including more number of related publications. The third limitation was the review process considered only peer-reviewed published articles on the English language. However, research on ecosystem services is rapidly changing and research publications are being published in a significant amount using other languages like Chinese, Spanish, and others. Other publications like proceedings, grey literature and policy documents, or publications written both in English and other languages were excluded. Therefore, the limitation was unavoidable and led to overlook some relevant publications.

Despite broad recognition of the benefits of ES, several knowledge gaps can be identified on the basis of the overview given in this article. Among them, existing studies on valuing and assessing RES fall short of the need to mainstreaming into decision-making and integrating into national-level environmental resource management strategies. This was due to the fact that valuing RES is not easy compared to other ES that has a direct link with human well-being. There was also the use of multiple ES classifications and naming that makes comparison and meta-analysis of studies and assessments more difficult. As per a prerequisite, designing a common ground that permits comparison between RES assessments from different study sites has become more urgent.

In the last decade, ecosystem service studies increased steadily, but relatively no significant number of studies were found from regulatory services, whereas the existing studies were concentrated on urban and forest ecosystems as they have more developed methods and link with human safety. Thus, the existing knowledge generated on the importance of RES is still limited and more research is needed to elucidate its synergy and tradeoff relation across space and time with other ES and human health.

We, therefore, propose that future research works should be painstakingly aiming to cover the RES that has local scale impacts such as pollination, pest regulation, disease regulation, and air quality regulating services. Besides, future studies should give priority for methodological development and proposing management options for improving the RES of ecosystems. Finally, most of the studies concentrated on secondary data and application of modeling to develop conceptual ideas even at local scale studies. Rather, scholars, therefore, are encouraged to integrate primary data for scrutinizing the link between human safety and RES.

Availability of data and materials

Not applicable.

Abbreviations

Ecosystem service

Millennium ecosystem assessment

Regulating ecosystem services

Search, appraisal, synthesis, analysis

The economics of ecosystems and biodiversity

Abson DJ, von Wehrden H, Baumgärtner S et al (2014) Ecosystem services as a boundary object for sustainability. Ecol Econ 103:29–37

Alamgir M, Pert PL, Turton SM (2014) A review of ecosystem services research in Australia reveals a gap in integrating climate change and impacts on ecosystem services. Int J Biodivers Sci Ecosyst Serv Manag 10(2):112–127

Article   Google Scholar  

Alamgir M, Turton SM, Macgregor CJ, Pert PL (2016) Assessing regulating and provisioning ecosystem services in a contrasting tropical forest landscape. Ecol Indic 64:319–334

Almeida CMVB, Mariano MV, Agostinho F et al (2018) Comparing costs and supply of supporting and regulating services provided by urban parks at different spatial scales. Ecosyst Serv 30:236–247

Balvanera P, Uriarte M, Almeida-Leñero L et al (2012) Ecosystem services research in Latin America: the state of the art. Ecosyst Serv 2:56–70

Beaumont NJ, MC Austen, JP Atkins, D Burdon, S Degraer, TP Dentinho, S Derous, P Holm, T Horton, E van Ierland, AH Marboe, DJ Starkey, M Townsend, and T Zarzycki (2007) “Identification, Definition and Quantification of Goods and Services Provided by Marine Biodiversity. Implications for the Ecosystem Approach”. Marine Pollution Bulletin 54(3):253–65.

Bicking S, Burkhard B, Kruse M, Müller F (2018) Mapping of nutrient regulating ecosystem service supply and demand on different scales in Schleswig-Holstein, Germany. One Ecosystem 3:e22509

Boyd J, Banzhaf S (2007) What are ecosystem services? The need for standardized environmental accounting units. Ecol Econ 63:616–626

Braat LC, de Groot R (2012) The ecosystem services agenda: bridging the worlds of natural science and economics, conservation and development, and public and private policy. Ecosyst Serv 1:4–15

Brainard DC, Bryant A, Noyes DC, Haramoto ER, Szendrei Z (2016) Evaluating pest-regulating services under conservation agriculture: a case study in snap beans. Agric Ecosyst Environ 235:142–154

Brander L, Brouwer R, Wagtendonk AJ (2013) Economic valuation of regulating services provided by wetlands in agricultural landscapes: a meta-analysis. Ecol Eng 56:89–96

Burkhard B, Kroll F, Nedkov S, Müller F (2012) Mapping ecosystem service supply, demand and budgets. Ecol Indic 21:17–29

Caro C, Cunha PP, Marques J, Teixeira Z (2020) Identifying ecosystem services research hotspots to illustrate the importance of site-specific research: an Atlantic coastal region case study. Environ Sustain Indic 6:100031

Hepcan CC, Hepcan S (2018) Assessing regulating ecosystem services provided by the Ege University Rectorship Garden. Urban For Urban Green 34:10–16

Costanza R, d'Arge R, De Groot R et al (1997) The value of the world’s ecosystem services and natural capital. Nature 387:253–260

Costanza R, de Groot R, Braat L et al (2017) Twenty years of ecosystem services: how far have we come and how far do we still need to go? Ecosyst Serv 28:1–16

Daily GC (1997) Nature’s services: societal dependence on natural ecosystems. Island Press, Washington, DC

Davies HJ, Doick KJ, Hudson MD, Schreckenberg K (2017) Challenges for tree officers to enhance the provision of regulating ecosystem services from urban forests. Environ Res 156:97–107

Deal RL, Cochran B, LaRocco G (2012) Bundling of ecosystem services to increase forestland value and enhance sustainable forest management. Forest Policy Econ 17:69–76

Droste N, D’Amato D, Goddard JJ (2018) Where communities intermingle, diversity grows – the evolution of topics in ecosystem service research. PLoS ONE 13(9):e0204749

Egoh B, Drakou E, Dunbar M, Maes J, Willemen L (2012) Indicators for mapping ecosystem services: a review JRC scientific and policy reports. Luxembourg 10:41823

Google Scholar  

Egoh B, Rouget M, Reyers B et al (2007) Integrating ecosystem services into conservation assessments: a review. Ecol Econ 63(4):714–721

Englund O, Berndes G, Cederberg C (2017) How to analyse ecosystem services in landscapes—a systematic review. Ecol Indic 73:492–504

Fagerholm N, Torralba M, Burgess PJ, Plieninger TA (2016) A systematic map of ecosystem services assessments around European agroforestry. Ecol Indic 62:47–65

Fisher B, Turner RK, Morling P (2009) Defining and classifying ecosystem services for decision making. Ecol Econ 68:643–653

Fletcher S, Saunders J, Herbert R (2011) A review of the ecosystem services provided by broad-scale marine habitats in England’s MPA network. J Coast Res:378–383

Ghazi H, Messouli M, Yacoubi Khebiza M, Egoh BN (2018) Mapping regulating services in Marrakesh Safi region - Morocco. J Arid Environ 159:54–65

Giedych R, Maksymiuk G (2017) Specific features of parks and their impact on regulation and cultural ecosystem services provision in Warsaw, Poland. Sustainability 9(5):792

Goslee K, Walker SM, Grais A, Murray L, Casarim F, Brown S (2016) Module C-CS: calculations for estimating carbon stocks

Grant MJ, Booth A (2009) A typology of reviews: an analysis of 14 review types and associated methodologies. Health Inf Libr J 26(2):91–108

Grêt-Regamey A, Brunner SH, Altwegg J, Bebi P (2013) Facing uncertainty in ecosystem services-based resource management. J Environ Manag 127:S145–S154

Haines-Young R, Potschin M (2011) Common international classification of ecosystem services (CICES): 2011 Update. Report to the European Environmental Agency, Nottingham

Heink U, Hauck J, Jax K, Sukopp U (2016) Requirements for the selection of ecosystem service indicators–the case of MAES indicators. Ecol Indic 61:18–26

Howe C, Suich H, Vira B, Mace GM (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. Glob Environ Chang 28:263–275

Ifatimehin O (2014) Ecosystem Regulatory services and human comfort in an outdoor environment of Lokoja, Nigeria. Br J Appl Sci Technol 4(18):2576–2589

Inkoom JN, Frank S, Greve K, Furst C (2018) A framework to assess landscape structural capacity to provide regulating ecosystem services in West Africa. J Environ Manag 209:393–408

Kandziora M, Burkhard B, Müller F (2013) Interactions of ecosystem properties, ecosystem integrity and ecosystem service indicators—a theoretical matrix exercise. Ecol Indic 28:54–78

Keeler BL, Polasky S, Brauman KA et al (2012) Linking water quality and well-being for improved assessment and valuation of ecosystem services. Proc Natl Acad Sci 109(45):18619–18624

Kong F, Sun C, Liu F et al (2016) Energy saving potential of fragmented green spaces due to their temperature regulating ecosystem services in the summer. Appl Energy 183:1428–1440

Krkoška Lorencová E, Harmáčková ZV, Landová L, Pártl A, Vačkář D (2016) Assessing impact of land use and climate change on regulating ecosystem services in the Czech Republic. Ecosyst Health Sustain 2(3):e01210

La Notte A, D’Amato D, Mäkinen H et al (2017) Ecosystem services classification: a systems ecology perspective of the cascade framework. Ecol Indic 74:392–402

Larondelle N, Haase D, Kabisch N (2014) Mapping the diversity of regulating ecosystem services in European cities. Glob Environ Chang 26:119–129

Laurans Y, Rankovic A, Billé R, Pirard R, Mermet L (2013) Use of ecosystem services economic valuation for decision making: questioning a literature blindspot. J Environ Manag 119:208–219

Lautenbach S, Mupepele A-C, Dormann CF et al (2019) Blind spots in ecosystem services research and challenges for implementation. Reg Environ Chang:1–22

Lee H, Lautenbach S (2016) A quantitative review of relationships between ecosystem services. Ecol Indic 66:340–351

Li R, Zheng H, Lv S, Liao W, Lu F (2018) Development and evaluation of a new index to assess hydrologic regulating service at sub-watershed scale. Ecol Indic 86:9–17

Liquete C, Piroddi C, Drakou EG et al (2013) Current status and future prospects for the assessment of marine and coastal ecosystem services: a systematic review. PLoS One 8(7):e67737

Article   CAS   Google Scholar  

LoTemplio S, Reynolds TW, Wassie Eshete A, Abrahams M, Bruesewitz D, Wall JA (2017) Ethiopian Orthodox church forests provide regulating and habitat services: evidence from stream sediment and aquatic insect analyses. Afr J Ecol 55(2):247–251

Luederitz C, Brink E, Gralla F et al (2015) A review of urban ecosystem services: six key challenges for future research. Ecosyst Serv 14:98–112

MA (2005) Ecosystems and human well-being: synthesis. Island Press, Washington, DC

Maes J, Egoh B, Willemen L et al (2012) Mapping ecosystem services for policy support and decision making in the European Union. Ecosyst Serv 1:31–39

Malinauskaite L, Cook D, Davíðsdóttir B, Ögmundardóttir H, Roman J (2019) Ecosystem services in the Arctic: a thematic review. Ecosyst Serv 36:100898

Malinga R, Gordon LJ, Jewitt G, Lindborg R (2015) Mapping ecosystem services across scales and continents – a review. Ecosyst Serv 13:57–63

Manes F, Marando F, Capotorti G et al (2016) Regulating ecosystem services of forests in ten Italian metropolitan cities: air quality improvement by PM 10 and O 3 removal. Ecol Indic 67:425–440

Marando F, Salvatori E, Sebastiani A, Fusaro L, Manes F (2019) Regulating ecosystem services and green infrastructure: assessment of urban heat island effect mitigation in the municipality of Rome, Italy. Ecol Model 392:92–102

Martínez-Harms MJ, Balvanera P (2012) Methods for mapping ecosystem service supply: a review. Int J Biodivers Sci Ecosyst Serv Manag 8(1-2):17–25

McDonough K, Hutchinson S, Moore T, Hutchinson J (2017) Analysis of publication trends in ecosystem services research. Ecosyst Serv 25:82–88

Mengist W, Soromessa T (2019) Assessment of forest ecosystem service research trends and methodological approaches at global level: a meta-analysis. Environ Syst Res 8(1):22

Mengist W, Soromessa T, Legese G (2019a) Ecosystem services research in mountainous regions: a systematic literature review on current knowledge and research gaps. Sci Total Environ 702:134581

Mengist W, Soromessa T, Legese G (2019b) Method for conducting systematic literature review and meta-analysis for environmental science research. MethodsX:100777

Milcu A, Hanspach J, Abson D, Fischer J (2013) Cultural ecosystem services: a literature review and prospects for future research. Ecol Soc 18(3):UNSP 44

Missall S, Welp M, Thevs N, Abliz A, Halik Ü (2015) Establishment and maintenance of regulating ecosystem services in a dryland area of central Asia, illustrated using the Kökyar Protection Forest, Aksu, NW China, as an example. Earth System Dynamics 6(1):359–373

Moher D, Liberati A, Tetzlaff J, Altman DG (2010) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg 8(5):336–341

Nedkov, Stoyan and Benjamin Burkhard (2012) “Flood Regulating Ecosystem Services - Mapping Supply and Demand, in the Etropole Municipality, Bulgaria”. Ecological Indicators 21:67–79.

Nemec KT, Raudsepp-Hearne C (2013) The use of geographic information systems to map and assess ecosystem services. Biodivers Conserv 22(1):1–15

Oka C, Aiba M, Nakashizuka T (2019) Phylogenetic clustering in beneficial attributes of tree species directly linked to provisioning, regulating and cultural ecosystem services. Ecol Indic 96:477–495

Pan Y, Wu J, Xu Z (2014) Analysis of the tradeoffs between provisioning and regulating services from the perspective of varied share of net primary production in an alpine grassland ecosystem. Ecol Complex 17:79–86

Perevochtchikova M, Flores JÁH, Marín W, Flores AL, Bueno AR, Negrete IAR (2019) Systematic review of integrated studies on functional and thematic ecosystem services in Latin America, 1992–2017. Ecosyst Serv 36:100900

Richards DR, Edwards PJ (2017) Quantifying street tree regulating ecosystem services using Google Street View. Ecol Indic 77:31–40

Scholz T, Hof A, Schmitt T (2018) Cooling effects and regulating ecosystem services provided by urban trees—novel analysis approaches using urban tree cadastre data. Sustainability 10(3):712

Seppelt R, Dormann CF, Eppink FV, Lautenbach S, Schmidt S (2011) A quantitative review of ecosystem service studies: approaches, shortcomings and the road ahead. J Appl Ecol 48(3):630–636

Smith P, Ashmore MR, Black HI et al (2013) The role of ecosystems and their management in regulating climate, and soil, water and air quality. J Appl Ecol 50(4):812–829

Stürck J, Poortinga A, Verburg PH (2014) Mapping ecosystem services: the supply and demand of flood regulation services in Europe. Ecol Indic 38:198–211

Stürck J, Schulp CJE, Verburg PH (2015) Spatio-temporal dynamics of regulating ecosystem services in Europe – the role of past and future land use change. Appl Geogr 63:121–135

Sutherland IJ, Villamagna AM, Dallaire CO et al (2018) Undervalued and under pressure: a plea for greater attention toward regulating ecosystem services. Ecol Indic 94:23–32

Talbot CJ, Bennett EM, Cassell K et al (2018) The impact of flooding on aquatic ecosystem services. Biogeochemistry 141(3):439–461

Tancoigne E, Barbier M, Cointet J-P, Richard G (2014) The place of agricultural sciences in the literature on ecosystem services. Ecosyst Serv 10:35–48

Viglizzo EF, Jobbágy E, Ricard MF, Paruelo JM (2016) Partition of some key regulating services in terrestrial ecosystems: meta-analysis and review. Sci Total Environ 562:47–60

Villamagna AM, Angermeier PL, Bennett EM (2013) Capacity, pressure, demand, and flow: a conceptual framework for analyzing ecosystem service provision and delivery. Ecol Complex 15:114–121

Vo QT, Kuenzer C, Vo QM, Moder F, Oppelt N (2012) Review of valuation methods for mangrove ecosystem services. Ecol Indic 23:431–446

Walz U, Richter B, Grunewald K (2019) Indicators on the ecosystem service “regulation service of floodplains”. Ecol Indic 102:547–556

Wang J, Chen S, Wang M (2019) How do spatial patterns impact regulation of water-related ecosystem services? Insights from a new town development in the Yangtze River Delta, China. Sustainability 11(7):2010

Wangai PW, Burkhard B, Müller F (2016) A review of studies on ecosystem services in Africa. Int J Sustain Built Environ 5(2):225–245

Watson R, Albon S, Aspinall R et al (2011) UK National Ecosystem Assessment: understanding nature’s value to society. Synthesis of key findings. (eprints.lancs.ac.uk)

Weitzman J (2019) Applying the ecosystem services concept to aquaculture: a review of approaches, definitions, and uses. Ecosyst Serv 35:194–206

Weyland F, Mastrangelo ME, Auer AD et al (2019) Ecosystem services approach in Latin America: from theoretical promises to real applications. Ecosyst Serv 35:280–293

Download references

Acknowledgements

We thank the two anonymous reviewers for their suggestions and useful comments. We wish to thank both Addis Ababa University and Debre-Berhan University for the support of this initiative.

This research received no external funding.

Author information

Authors and affiliations.

Department of Natural Resource Management, Debre Berhan University, Debre Berhan, Ethiopia

Wondimagegn Mengist

Center for Environmental Science, Addis Ababa University, Addis Ababa, Ethiopia

Wondimagegn Mengist, Teshome Soromessa & Gudina Legese Feyisa

You can also search for this author in PubMed   Google Scholar

Contributions

MW had the initial idea and collected the related materials. ST and LG edited the manuscript and improved the language. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Wondimagegn Mengist .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare that they have no competing interests .

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Mengist, W., Soromessa, T. & Feyisa, G.L. A global view of regulatory ecosystem services: existed knowledge, trends, and research gaps. Ecol Process 9 , 40 (2020). https://doi.org/10.1186/s13717-020-00241-w

Download citation

Received : 22 April 2020

Accepted : 25 June 2020

Published : 23 July 2020

DOI : https://doi.org/10.1186/s13717-020-00241-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Ecosystem service indicators
• Less tangible benefits
• Regulatory ecosystem services
• Research trend
• Undervalued services

A Global Systematic Literature Review of Ecosystem Services in Reef Environments

Affiliations.

• 1 Universidade Federal do Oeste do Pará, Campus Oriximiná, PA, Brazil. [email protected].
• 2 Departamento de Ecologia e Zoologia, Universidade Federal de Santa Catarina, Florianópolis, SC, Brazil.
• 3 Laboratório de Ciências Ambientais, Universidade Estadual do Norte Fluminense, Campos dos Goytacazes, RJ, Brazil.
• 4 Departamento de Ecologia e Evolução, Universidade Federal de Santa Maria, Santa Maria, RS, Brazil.
• 5 Hawai'i Institute of Marine Biology, University of Hawai'i at Manoa, Kaneohe, HI, 96744, USA.
• 6 Programa de Pós Graduação em Ecologia, Universidade Federal de Santa Catarina, Florianópolis, SC, Brazil.
• 7 Instituto do Mar, Universidade Federal de São Paulo, Santos, SP, Brazil.
• 8 Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin, NT, Australia.
• 9 Departamento de Biologia Marinha, Universidade Federal Fluminense, Niterói, RJ, Brazil.
• 10 Centro de Biologia Marinha, Universidade de São Paulo, São Sebastião, SP, Brazil.
• PMID: 38006452
• DOI: 10.1007/s00267-023-01912-y

Ecosystem services (ES) embrace contributions of nature to human livelihood and well-being. Reef environments provide a range of ES with direct and indirect contributions to people. However, the health of reef environments is declining globally due to local and large-scale threats, affecting ES delivery in different ways. Mapping scientific knowledge and identifying research gaps on reefs' ES is critical to guide their management and conservation. We conducted a systematic assessment of peer-reviewed articles published between 2007 and 2022 to build an overview of ES research on reef environments. We analyzed the geographical distribution, reef types, approaches used to assess ES, and the potential drivers of change in ES delivery reported across these studies. Based on 115 articles, our results revealed that coral and oyster reefs are the most studied reef ecosystems. Cultural ES (e.g., subcategories recreation and tourism) was the most studied ES in high-income countries, while regulating and maintenance ES (e.g., subcategory life cycle maintenance) prevailed in low and middle-income countries. Research efforts on reef ES are biased toward the Global North, mainly North America and Oceania. Studies predominantly used observational approaches to assess ES, with a marked increase in the number of studies using statistical modeling during 2021 and 2022. The scale of studies was mostly local and regional, and the studies addressed mainly one or two subcategories of reefs' ES. Overexploitation, reef degradation, and pollution were the most commonly cited drivers affecting the delivery of provisioning, regulating and maintenance, and cultural ES. With increasing threats to reef environments, the growing demand for assessing the contributions to humans provided by reefs will benefit the projections on how these ES will be impacted by anthropogenic pressures. The incorporation of multiple and synergistic ecosystem mechanisms is paramount to providing a comprehensive ES assessment, and improving the understanding of functions, services, and benefits.

Keywords: Coastal livelihoods; Ecosystem benefits; Food security; Human well-being; Marine ecosystem services; Reef systems.

© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Publication types

• Systematic Review
• Anthozoa* / physiology
• Conservation of Natural Resources / methods
• Coral Reefs
• Models, Statistical

Grants and funding

• 442417/2019-5/Conselho Nacional de Desenvolvimento Científico e Tecnológico

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 07 May 2024

Effects of management practices on the ecosystem-service multifunctionality of temperate grasslands

• Franziska J. Richter   ORCID: orcid.org/0000-0001-7865-9903 1 ,
• Matthias Suter 2 ,
• Andreas Lüscher   ORCID: orcid.org/0000-0001-8158-1721 2 ,
• Nina Buchmann   ORCID: orcid.org/0000-0003-0826-2980 1 ,
• Nadja El Benni 3 ,
• Rafaela Feola Conz   ORCID: orcid.org/0000-0002-9793-5501 4 ,
• Martin Hartmann   ORCID: orcid.org/0000-0001-8069-5284 4 ,
• Pierrick Jan 5 &
• Valentin H. Klaus   ORCID: orcid.org/0000-0002-7469-6800 1 , 2  

Nature Communications volume  15 , Article number:  3829 ( 2024 ) Cite this article

1868 Accesses

69 Altmetric

Metrics details

• Agriculture
• Ecosystem services
• Grassland ecology

Human wellbeing depends on ecosystem services, highlighting the need for improving the ecosystem-service multifunctionality of food and feed production systems. We study Swiss agricultural grasslands to assess how employing and combining three widespread aspects of grassland management and their interactions can enhance 22 plot-level ecosystem service indicators, as well as ecosystem-service multifunctionality. The three management aspects we assess are i) organic production system, ii) an eco-scheme prescribing extensive management (without fertilization), and iii) harvest type (pasture vs. meadow). While organic production system and interactions between the three management aspects play a minor role, the main effects of eco-scheme and harvest type considerably shape single services. Moreover, the eco-scheme ‘extensive management’ and the harvest type ‘pasture’ enhance plot-scale ecosystem-service multifunctionality, mostly through facilitating cultural services at the expense of provisioning services. These changes in ecosystem-service supply occur mainly via changes in land-use intensity, i.e., reduced fertilizer input and harvest frequency. In conclusion, diversifying grassland management where this is currently homogeneous across farms and landscapes depicts an important first step to improve landscape-scale multifunctionality for sustainable grassland systems. To meet societal ecosystem services demand, the three studied management aspects can be systematically combined to increase ecosystem services that are in short supply.

Similar content being viewed by others

Economic value of three grassland ecosystem services when managed at the regional and farm scale

Nexus of grazing management with plant and soil properties in northern China grasslands

Grassland intensification effects cascade to alter multifunctionality of wetlands within metaecosystems

Introduction.

Providing sustainably produced food and feed while safeguarding ecosystem services is a primary global challenge 1 , 2 . Environmental sustainability issues of intensive production therefore set a spotlight on land management strategies to increase beneficial ecosystem services and reduce negative environmental impacts (disservices) of agriculture 3 . Before introducing agricultural policies that promote certain farming practices, the effectiveness of these practices needs to be assessed in terms of their individual and combined environmental benefits.

Grasslands are a major global land use, covering 70% of the global agricultural area 4 . Globally, grasslands are highly important for nutrition security as 20% of protein for human nutrition is derived from ruminants, which are to a large part fed from grasslands 5 , 6 , 7 , more than half of which (by area) are located on marginal land that cannot be used for crop production 8 . Further, grasslands contribute to human well-being by providing many ecosystem services other than food or feed provisioning, including supporting and regulating ecosystem services, such as water and climate regulation, as well as cultural ecosystem services by, for instance, contributing to visually pleasing landscapes 9 , 10 . Preserving and promoting the ability of grasslands to provide many ecosystem services in one area, i.e., high ecosystem-service multifunctionality 11 , will be crucial to support human well-being in a world faced with growing human population, urban growth, and climate change.

In many temperate regions, grasslands and their ecosystem services rely on either regular grazing by animals or mowing, as they would otherwise be encroached by shrubs and trees. However, widespread intensification of agricultural management in the form of increased fertilization as well as more frequent and earlier harvests has become a threat for grassland ecosystem-service multifunctionality, by heavily focusing on provisioning ecosystem services and neglecting other ecosystem services 12 , 13 , 14 . Agri-environmental strategies and policies therefore aim at enhancing ecosystem-service multifunctionality by regulating grassland management intensity, potentially resulting in losses in agricultural production.

Many of these agricultural and agri-environmental regulations target plot-scale grassland management, resulting in different plant communities and delivering different sets of ecosystem services and different levels of plot-scale multifunctionality 12 . The latter corresponds to ecosystem multifunctionality 11 and informs about how a broad set of ecosystem services is affected by a specific management practice. Knowledge on plot-scale effects of management on ecosystem services is further required to achieve multifunctionality on the landscape scale, resolving inevitable trade-off between ecosystem services at the plot scale 15 , 16 . However, given the many potentially interacting aspects that shape agricultural grassland management (i.e., mowing versus grazing, different fertilization levels, etc.), it has not yet been investigated how management intensity in concert with other key aspects of grassland management affect a broader range of ecosystem services and associated multifunctionality.

Here, we tested three aspects of grassland management that are widespread in their adoption and implemented independently from but alongside each other for their ability to increase ecosystem-service multifunctionality. We analyzed the impact of (i) organic production, (ii) the eco-scheme “extensive management”, and (iii) the harvest type, i.e., the option to either use the land as pasture (grazing predominant) or as meadow to feed the grass offsite (mowing predominant), on 22 ecosystem-service indicators and resulting plot-scale multifunctionality. While organic management and eco-scheme “extensive management” are instruments of agri-environmental policies that financially compensate farmers for restricting management intensity, the harvest type is usually set by farmers according to their individual farming approach on the given land.

Organic management receives a lot of attention, for instance in the Farm to Fork strategy of the Common Agricultural Policy of the European Union 17 , as it depicts a farm-level production system (hereafter “Production system organic versus non-organic”) that minimizes synthetic inputs to promote healthy soils and ecosystems 18 . However, organic management has never been tested for its ability to enhance multiple ecosystem services in grassland ecosystems 19 . For arable crops, organic management has been found to benefit ecosystem-service multifunctionality, while reducing yields by 5–35% 20 , 21 .

Many European countries provide economic incentives for extensive grassland management (hereafter “Eco-scheme extensive management”: yes versus no), with the aim of enhancing biodiversity and potentially also specific ecosystem services such as water quality 22 , 23 , 24 . Existing studies on the effect of grassland eco-schemes focused mainly on biodiversity while the impact of these schemes on other ecosystem services has not been as thoroughly investigated so far. Recent studies found several regulating, supporting, and cultural ecosystem services to be decreased at high-management intensity, indicating the importance of extensive management for non-production ecosystem-service multifunctionality 12 , 13 . Yet, studies assessing how the effect of extensive management on the simultaneous supply of multiple ecosystem services interacts with, e.g., the harvest type, are needed to understanding trade-offs and synergies in ecosystem services provision linked to this widespread policy tool 13 .

A further key aspect of grassland management concerns the predominant type of biomass removal or harvest (hereafter “Harvest type pasture versus meadow”). The Harvest type can shape grasslands, as grazing animals are selective for or against certain plant species 25 , which can lead to increasing abundance of unwanted species, while mowing is unselective and impacts all species equally. Meadows and pastures thus show distinct differences in vegetation composition but also microbial processes, which likely affects ecosystem services 26 , 27 . In addition, trampling by livestock can lead to disservices such as erosion and low soil organic carbon as a consequence of sward damage 28 . However, despite its ubiquitous relevance, the effect of Harvest type on ecosystem-service multifunctionality is currently unknown.

To address the question of how these three widespread management aspects, as well as the interactions among them, influence grassland ecosystem services and related multifunctionality, we assessed 22 ecosystem-service indicators in 86 managed grasslands in the Canton of Solothurn, Switzerland (Supplementary Table  S1 ). These 22 indicators correspond to 12 ecosystem services, following the common international classification of ecosystem services (CICES 29 ; Fig.  1a ), as in some cases several indicators reflect different components of one ecosystem services 11 , 30 . Our study design allowed us to investigate all possible combinations of the management aspects of interest, namely Production system (organic vs. non-organic), Eco-scheme (extensive management yes vs. no) and Harvest type (pasture vs. meadow) on grassland plots (Fig.  1b ).

a From left to right: indicators grouped according to the corresponding ecosystem service defined by CICES 29 and corresponding ecosystem-service category. b From top to bottom: brief definition of the three management aspects studied: Production system, Eco-scheme, and Harvest type. All 22 ecosystem-service indicators were measured for the eight possible combinations of Production system, Eco-scheme, and Harvest type. Total number of study plots was 86 (see Supplementary Table  S1 for number of plots per combination of management aspects).

Our objectives were to first analyze the effect of management aspects on single ecosystem-service indicators using multivariate regression. Second, we assessed how the effects of the three management aspects on single ecosystem services act via changes in mowing frequency, fertilizer amount and grazing intensity, the three most decisive management actions in Central European grasslands 31 . Third, we tested the effect of the three management aspects on plot-scale ecosystem-service multifunctionality by using a log response ratio approach. These consecutive analytical steps allowed us to assess if and how Production system, Eco-scheme and Harvest type affect grassland ecosystem-service multifunctionality. Results of this study can, thus, inform and support improving grassland management and related agri-environmental policies in optimizing grassland ecosystem-service provision and thus improving the multifunctionality of agricultural landscapes. Insights into the relationships between single practices and ecosystem services allow farmers and other decision-makers to adapt grassland management to support a specific ecosystem service or even ecosystem-service multifunctionality at a given site.

Impact of management aspects on ecosystem-service indicators

The 22 ecosystem-service indicators hardly differed between Production systems (organic vs. non-organic), but often between extensive Eco-scheme vs. non-Eco-scheme grasslands, and between the two Harvest types (meadow vs. pasture; Fig.  2 ). For instance, biomass yield and digestibility were higher in non-Eco-scheme grasslands, while Eco-scheme grasslands performed better regarding less nitrogen (N) leaching and less surface P, our measure to assess eutrophication risk. Eco-scheme pastures performed especially well regarding edible plant abundance, iconic fungi, and livestock presence (Fig.  2 ). The main effects and interactions of the three management aspects on the 22 ecosystem-service indicators were evaluated with generalized linear latent variable models (GLLVM 32 ), which revealed that Eco-scheme had the strongest influence on the ecosystem-service indicators, while interactions between the management aspects were generally not relevant to explain these indicators (Fig.  3 and Supplementary Table  S2 ). Eco-scheme extensive management significantly improved ten out of 22 ecosystem-service indicators belonging to supporting/regulating and cultural ecosystem services, such as plant richness, proportion of AM fungi, and esthetics (Fig.  3 ). In comparison, management without Eco-scheme promoted six out of 22 ecosystem-service indicators, including both provisioning and some supporting/regulating indicators, such as earthworms and fewer weeds. Harvest type had a smaller influence on ecosystem-service indicators than the Eco-scheme. Use as pasture promoted five indicators (e.g., digestibility and edible plants), while use as meadow promoted five indicators (e.g., biomass yield and lower N 2 O emissions). Production system significantly affected only two ecosystem-service indicators: Organic management increased the relative abundance of AM fungi and led to less nitrate leaching compared to non-organic management. Yet, no ecosystem-service indicator significantly decreased (worsened) as a response to organic management (Fig.  3 ). Taken together, while Eco-scheme and Harvest type affected many of the ecosystem-service indicators, the Production system had only a marginal influence. This observation was consistent across the other two management aspects (no significant interactions between the Production system and Eco-scheme and Harvest type). The finally selected GLLVM also included three environmental co-variables to account for potential confounding of the environment with the management aspects (see Supplementary Table  S2 for the model selection summary). Here, soil pH, sand content, and elevation affecting six, seven, and eight ecosystem-service indicators, respectively (see Supplementary Fig.  S2 for the coefficient plots, and Supplementary Fig.  S3 for the correlations among all tested environmental variables). Noteworthy, although the environmental variables explained some variation in the data, their addition to the GLLVM had only a marginal impact on the effects of the management aspects compared with a model without environmental variables (see Supplementary Fig.  S4 ). This is because the management aspects were the main drivers of plot-scale responses and well distributed across the environmental gradient of the study region.

Bars denote the mean value (with standard error) for each indicator and the combination of management aspects (Production system: organic vs. non-organic; Eco-scheme extensive management: yes vs. no; Harvest type: pasture vs. meadow). Values are maximum-scaled per indicator (over the whole dataset) and reversed for disservices; colors correspond to the ecosystem services according to CICES (see Fig.  1 ). Replicate numbers (grasslands) are given in the top left corner of the respective barplot. See Fig.  3 for statistical tests on management effects on all indicators. Source data are provided as a Source Data file.

Significant effects are shown in black ( P  < 0.05). Regression estimates (points) and 95% confidence intervals (bars) derived from testing the main effects of Production system ( a ), Eco-scheme ( b ), and Harvest type ( c ) on the 22 max-scaled ecosystem-service indicators. Color coding of icons for ecosystem-service indicators corresponds to the respective ecosystem service according to CICES (see Fig.  1 ). Ecosystem-service indicators in italics have been reversed to show services instead of disservices. This model included three environmental variables, soil pH, sand content, and elevation, the coefficient plots of which can be found in Supplementary Fig.  S2 . N  = 86 grasslands. Source data are provided as a Source Data file.

Effects of management aspects as explained by management intensity variables

To explore the extent to which the 17 statistically significant effects of the three management aspects (observed in the GLLVM, Fig.  3 ) on the ecosystem-service indicators could be explained by the management intensity variables fertilizer amount, mowing frequency, and grazing intensity, we used standardized structural equation models (SEMs, Fig.  4 ). The basic structure of the SEM used for all 17 ecosystem-service indicators is shown in Fig.  4a (and full SEMs with model fit statistics in Supplementary Fig.  S5 ). Note that inclination of the grasslands was significantly related to Eco-scheme and pasture (Fig.  4a ), while there was no such effect of inclination on Production system because the sampling design assured pairs of organic and non-organic grasslands to have similar topography. Elevation and northness were also tested but removed from the SEM because they did not significantly affect any of the management aspects.

Indirect effects of the Production system, Eco-scheme, and Harvest type act via fertilizer N (fertilization intensity), number of cuts (cutting frequency), and grazing intensity (livestock units × grazing days) on the max-scaled ecosystem-service indicators. Tested only for the 17 ecosystem-service indicators significantly influenced by at least one of the three management aspects (via GLLVM see Fig.  3 ). a This basic SEM model was used for every ecosystem-service indicator, with red arrows denoting decreasing, blue-gray arrows increasing effects, and light gray dotted arrows insignificant effects ( P  > 0.05). χ 2 statistic, comparative fit index (CFI) and standardized root mean-squared residual (SRMR) of the basic model are given. Dark gray solid arrows in the lower part of the SEM show direct and dashed arrows indirect effects on the ecosystem-service indicators via fertilizer N, number of cuts, and grazing intensity. These direct and indirect effects are shown in ( b ) with filled symbols, indicating the size of direct and indirect effects from a significant path, and non-filled symbols from insignificant paths. Besides inclination, elevation was also included in the initial SEM but was removed because it did neither significantly affect the three management aspects nor the three measures of management intensity. See appendix for full SEMs and fit indices (Supplementary Fig.  S5 ). Units for the management intensity variables are fertilizer N: plant-available N in kg ha −1 year −1 , number of cuts: cuts year −1 , and grazing intensity: livestock unit days ha −1 year −1 . N  = 86 grasslands. Source data are provided as a Source Data file.

Eco-scheme extensive and Harvest-type pasture showed rather strong effects, decreasing grassland land-use intensity with the obvious exception of the Harvest-type pasture that increased grazing intensity on the cost of cutting frequency. Organic management only decreased fertilization but not mowing and grazing intensities (Fig.  4a ). Organic pastures and meadows received on average significantly less available N via fertilization (46.3 ± 52.4 kg ha −1 , 82.6 ± 42.8 kg ha −1 , mean ± SD) than non-organic pastures and meadows (75.7 ± 55.8 kg ha −1 ,111.6 ± 55.7 kg ha −1 ; Fig.  4a and Supplementary Table  S1 ). Of the N from fertilizer on non-organic grasslands, only about 20% was mineral (synthetic) fertilizer. Note that these numbers refer only to grasslands without Eco-scheme, as grasslands under Eco-scheme did not receive any organic or mineral fertilizer as required by the respective agricultural policy (Fig.  1b ). Across all grasslands, mowing frequency was positively related to fertilization intensity (Spearman rho  = 0.41, P  < 0.001), but negatively to grazing intensity (Spearman rho  = −0.72, P  < 0.001; Supplementary Fig.  S6 ). Grazing intensity and fertilization were uncorrelated ( P  > 0.1).

Supporting the GLLVM results, organic management generally showed fewer significant effects on ecosystem-service indicators than Harvest type and Eco-scheme. However, via the effect of decreasing fertilization intensity, organic management impacted eight of the 17 indicators (Fig.  4b ); the respective effect sizes were, however, small in all eight cases. Eco-Scheme and Harvest type significantly affected almost all the 17 ecosystem-service indicators (16 and 12, respectively), either directly or indirectly, and with clearly bigger effect sizes than organic management.

The reductions in land-use intensity by the management aspects in turn had different subsequent effects on individual ecosystem-service indicators. For example, while the two indicators for provisioning services decreased with reduced intensity, most non-provisioning services (e.g., AM fungi, less Surface P, lower N 2 O emissions) increased with a reduction in management intensity (Fig.  4b ). In some cases, indirect positive and negative effects on management intensity occurred simultaneously for one ecosystem-service indicator in the SEMs, leading to an insignificant overall effect of the respective management aspect in the GLLVM (Fig.  3 ). For instance, Eco-scheme had a negative impact on livestock presence via reduced fertilization intensity. At the same time, it increased livestock presence via reducing the cutting frequency (Fig.  4b ). Thus, the overall effect of Eco-scheme on livestock presence remained insignificant (Fig.  3 ). The effects of the management aspects on individual ecosystem-service indicators acting via all three measures of land-use intensity underline the general importance of land-use intensity for the majority of grassland ecosystem services studied here.

Effects of management aspects on ecosystem-service indicators not acting via the intensities of mowing, fertilization and grazing appeared as direct effects in the SEMs (Fig.  4b ) and cannot be specified further. Direct effects occurred for slightly more than half of the indicators studied and were partly positive and partly negative. Most direct effects were found for Eco-scheme, followed by Harvest type. Noteworthy, Production system did not show any significant direct effect.

Effects of management aspects on ecosystem-service multifunctionality

To evaluate overall plot-scale multifunctionality, ecosystem-service indicators were grouped according to CICES (Fig.  1 ), and their multifunctionality was assessed by the mean log response ratio (MLRR) of the three management aspects (see “Methods” in Supplementary Material for details). Effects on overall ecosystem-service multifunctionality were larger for Eco-scheme and Harvest Type than for the Production system, which had no significant effect (Fig.  5 ). Despite diverging responses of single ecosystem services to Eco-scheme and Harvest-Type pasture, overall ecosystem-service multifunctionality significantly increased with these two management practices, highlighting that grassland management can considerably affect multifunctionally at the plot scale (Fig.  5a ).

Effects were separated into overall multifunctionality (displayed in the shaded areas) and multifunctionality of each of the three ecosystem-service categories, i.e., provisioning, supporting/regulating, and cultural. LRRs of the 12 single ecosystem services according to CICES shown as colored symbols. Error bars represent 95% confidence intervals based on bootstrapping. Colors of the points correspond to the respective indicators used for one distinct ecosystem service, and the shapes of the points correspond to the ecosystem-service category (Fig.  1 ). N  = 86 grasslands. Source data are provided as a Source Data file.

For Eco-scheme and Harvest type, a clear trade-off between ecosystem-service categories was observed: Eco-scheme, as well as Harvest-type pasture, increased cultural ecosystem services on average by 43% and 73%, respectively, while decreasing provisioning ecosystem services by −40% and −11% (Fig.  5b ). Eco-scheme also promoted the category of supporting/regulating ecosystem services by on average 36%, whereas Harvest type did not significantly affect this aspect of plot-scale multifunctionality due to weak and simultaneous positive and negative effects on single ecosystem services. Note that the strong effect of pasture on the cultural ecosystem-service category was partly ruled by a strong positive effect of pasture on the ecosystem services “heritage and culture”, which includes the ecosystem-service indicator “livestock presence”.

We found the three major grassland management aspects studied to differently affect single ecosystem services and ecosystem-service multifunctionality at the plot-level. This insight in effects of grassland management, as shaped by agricultural policies and local decision-making, is required to take informed action to maintain and enhance landscape-scale multifunctionality and meeting societal needs that go beyond food production. While the Production system organic management did not affect ecosystem-service multifunctionality due to small effects on individual ecosystem services, the Eco-scheme of extensive grassland management had strong positive effects on non-provisioning ecosystem services and on multifunctionality, but decreased provisioning ecosystem services. The Harvest-type pasture was overall more beneficial for ecosystem-service multifunctionality than meadow, although different ecosystem-service indicators were promoted by either pasture or meadow. Surprisingly, we did not observe a major importance of interacting effects of the management aspects on ecosystem services. This underlines the relevance of each separate management aspect for ecosystem services and the option to freely combine these aspects to achieve the desired set of ecosystem services. Mechanistically, land-use intensity was found to be the key driver of single ecosystem services and related multifunctionality, as well as of the trade-offs observed between provisioning and especially cultural ecosystem services. Thus, the impact of the three management aspects on plot-scale ecosystem-service multifunctionality was closely related to lowering land-use intensity, albeit to very different degrees, as will be discussed in the following.

The Production system organic management appeared to play a minor role in increasing plot-level ecosystem-service multifunctionality in temperate grasslands. Organic grassland farming improved two out of the 22 indicators and did not significantly improve overall multifunctionality. However, importantly, organic farming did not have any significant negative effects on ecosystem-service indicators or multifunctionality, but showed a tendency towards lower biomass production. Interestingly, our SEM analysis did not find any direct effect of organic grassland farming on the studied ecosystem services (Fig.  4b ). The overall small effect of Production system is most likely due to the rather small differences in management intensity between organic and non-organic grasslands. Yet, organic management reduced fertilization intensity in non-Eco-scheme grasslands, in which fertilization was generally allowed, by on average 32% less available N compared to non-organic management. This lower land-use intensity of organic grassland farming is connected to the ban of synthetic fertilizers and lower limits for organic fertilization. It was previously observed in other contexts 33 , 34 and could directly be responsible for lower N 2 O emissions from organic grasslands. As lower N fertilization also relates to lower P input, this might further explain the higher abundance of AM fungi in organic grassland soils, indicating lower soil P availability than in intensively fertilized conventional soils.

The small benefits of organic management observed here close the research gap concerning the portfolio of ecosystem services supplied by organic grasslands, and are in line with results from croplands, in which organic management also appeared to play a minor role for improving ecosystem services. For croplands, increases in plot-scale ecosystem-service multifunctionality under organic management have been observed in some cases 20 , 35 , whereas in other cases, only a small number of individual ecosystem-service indicators improved, without a clear impact on ecosystem-service multifunctionality 36 , 37 . The overall weak effect of organic management on plot-scale grassland multifunctionality in our study acted via the slight decrease in fertilization intensity. This highlights the importance of considering regional and/or national fertilization standards when extending our findings to other places or systems, because the use of mineral fertilizers in grassland farming and related differences in management intensity between organic vs. non-organic grasslands can vary considerably among countries 38 , 39 . In Switzerland, grassland management is on average mid-intensive, with less fertilizer input than for instance in Germany, France, Belgium and the Netherlands, but more than in Estonia and Czech Republic 40 . Concerning pesticide applications, its use in Switzerland is lower compared to that in Germany, France, Belgium and Czech Republic, but higher than that in the Netherlands and Estonia 40 . Thus, greater differences in land-use intensity between organic and non-organic management likely lead to greater differences in plot-level ecosystem-service provision than observed here. This was, for example, shown for intensively managed organic vs. non-organic grasslands in the Netherlands 41 . In conclusion, it can be assumed that if organic and conventional grassland systems differ significantly in management intensity, it is highly likely that this will translate into benefits for especially non-provisioning ecosystem services in the less intensively managed system.

Our study provides evidence for a strong positive effect of the Eco-scheme extensive grassland management on ecosystem-service multifunctionality, especially of cultural ecosystem services, at the plot scale. This finding is of particular relevance for managing ecosystem services in landscapes dominated by intensive grassland management. The higher plot-scale multifunctionality observed should not be mistaken as the overall best way to manage grasslands, but suggests that Eco-scheme extensive management results in overall less trade-offs among the services studied. Yet, the significant increase in ecosystem-service multifunctionality comes at the cost of the provisioning ecosystem services, introducing a strong trade-off between regulating and cultural ecosystem services on the one hand, and provisioning ecosystem services on the other hand, is in accordance with previous ecosystem services research 12 , 13 , 14 . While we did observe that the Eco-scheme extensive management had a positive effect on many supporting/regulating ecosystem-service indicators, four of these indicators such as weed control and N 2 fixation were, however, lower in Eco-scheme grasslands and promoted by more intensive management. This is in line with a previous study finding some supporting and regulating ecosystem services to be increased with land-use intensity 42 . In the latter study, these services belonged to a group of ecosystem functions and processes that depend on high nutrient input such as nitrification and earthworm abundances 43 , 44 , 45 . Here, further aspects of intensive management like early harvest dates (e.g., less invertebrate herbivory 46 ) and weeding activities might also play a role, as farmers seem to accept more (potentially ecologically valuable) weeds in extensively managed grasslands, while focusing weed management on non-Eco-scheme (intensive) grasslands. In the case of N 2 fixation, the indicator used was strongly driven by biomass production, explaining the positive influence of non-Eco-scheme management and related fertilizer inputs.

In addition to lower management intensity, the studied Eco-scheme extensive management affected several ecosystem-service indicators via direct effects. While these direct effects cannot be finally explained with our assessment, we can conclude that they must act independently from current management intensity and might thus be related to land-use history, harvest and fertilizer dates, soil properties, or plant community composition. In line with the positive effect of inclination on the uptake of Eco-scheme extensive management in this study, indirect effects acting via site history such as long-term extensive management were suggested to play a crucial role in high plant diversity in permanent grasslands in Switzerland 47 . Overall, the positive effect of Eco-scheme on plot-scale ecosystem-service multifunctionality can be seen as further evidence justifying payments to farmers for such extensively managed land, which was originally designed for biodiversity support 48 .

The Harvest type, i.e., whether farmers decide to primarily graze (pasture) or mow a grassland (meadow), influenced many ecosystem-service indicators. Moreover, use as pasture promoted overall plot-scale ecosystem-service multifunctionality, especially regarding cultural ecosystem services. This effect was largely facilitated by pastures having highest values for the ecosystem-service indicator livestock presence, which has been observed to positively contribute to cultural ecosystem services 49 , 50 , especially heritage and recreation. This case of one indicator strongly driving a measure of multifunctionality, as well as the reasoning that multifunctionality is strongly influenced by the choice of indicators, points to one of the drawbacks of the frequently applied averaging approach: The average index operates as black box regarding the contributions of single indicators 51 , 52 . Yet, such issues can be easily detected and put into context by assessing single ecosystem services indicators and the using the MLRR approach, which allows for a transparent assessment of the contribution of single ecosystem services to overall multifunctionality. In addition, and similar to organic versus non-organic grasslands, pastures received on average slightly less fertilizer N than meadows, which constituted a weak trade-off between provisioning and cultural ecosystem services as discussed before.

Half of the ecosystem-service indicators showing a statistically significant response benefited from use as pasture, while the other half benefited from use as meadow (Fig.  3c ). These diverging effects of Harvest types are in line with previous findings. One study 53 , for instance, found a positive influence of grazing on ecosystem-service multifunctionality, whereas another 54 , using a different set of indicators, observed a decrease of ecosystem-service multifunctionality for grazed grasslands. Yet, other studies found grazing to have less negative or more positive effects on different aspects of grassland biodiversity compared to mowing 55 , 56 . This, together with effects of trampling and unselective mowing versus highly selective grazing differently shaping plant communities and their traits 57 , likely explains the differences in ecosystem services observed between the two Harvest types. For example, the negative effect of grazing on earthworms was most probably due to soil compaction by trampling livestock 58 , which has also been shown to potentially reduce yields 59 . On the other hand, trampling and selective grazing by livestock will have increased plant richness 47 .

The fact that Harvest type significantly influenced many single ecosystem services and impacted ecosystem-service multifunctionality shows that this aspect of grassland management could indeed be an impactful lever in adjusting ecosystem-service supply in a given area, depicting a relatively easy-to-implement tool to enhance cultural ecosystem services and landscape-scale ecosystem-service multifunctionality. Our study thus implies that landscapes dominated by grassland-based livestock systems relying on outdoor grazing will deliver a set of ecosystem services less supported by livestock systems with all-year indoor feeding.

The inevitable trade-offs we observed among different sets of ecosystem services lead to the conclusion that finding a one-type-fits-all grassland management is impossible, and that multifunctionality needs to be finally achieved at the landscape scale by allocating different management to different areas within the landscape (i.e., spatial segregation of ecosystem-service production) 11 . Yet, only a well-informed use of different management approaches, as provided by our study, can optimize ecosystem-service multifunctionality as desired by the local stakeholders 15 . To do this effectively, the ecosystem-service demand and priorities of local stakeholders have to be translated into a regional management plan to optimize the ecosystem-service provision 14 , 60 , 61 , as the stakeholders’ rating of the importance of a given ecosystem service differs according to region and context 61 . Thus, in addition to our plot-level results, it is necessary to adopt a wider view that includes farm- and landscape-scale drivers, as, for example, not only landscape composition but also configuration is important for ecosystem-service provision.

Regarding organic management, while we observed very weak effects of this management aspect on plot-level ecosystem services, organic management system could have further effects on ecosystem services at farm and landscape scales. For example, different feed origin and composition between organic and non-organic management systems have been shown to lead to beneficial effects of organic management on ecosystem services 62 . Furthermore, Swiss organic farms were shown to have a higher proportion of land under extensive Eco-schemes than conventional farms 63 , indicating farm-level benefits of organic management for biodiversity, cultural ecosystem services and ecosystem-service multifunctionality.

A further way the landscape scale should be considered when interpreting these plot-level results concerns the fact that grassland management is not distributed uniformly or randomly throughout a landscape. Eco-schemes and pastures tend to be implemented on agriculturally less favorable land, located at slopier sites 64 , 65 . Slopier sites have generally less favorable soil conditions and are harder to manage, resulting in less potential for intensification. The correlation of Eco-scheme and pasture with topography in the present study makes it difficult to fully disentangle management and topographic effects on ecosystem services, but on the other hand represents the real-world conditions governing the distribution of grassland types in the landscape as affected by farmers’ choices and the uptake of agri-environmental policies.

Our study showed that extensive Eco-scheme management and Harvest type (pasture versus meadow) were key determinants of individual ecosystem services and ecosystem-service multifunctionality in Swiss agricultural grasslands. This highlights the impact of agricultural policies and farmers’ decisions on grassland ecosystem-service supply. As no strong interacting effects of the management aspects studied were observed, these practices can be freely combined to achieve the desired set of services. This way, our plot-level outcomes can directly translate into action for landscape-scale management for ecosystem-service multifunctionality.

A main underlying driver of the improvements in ecosystem services was a decrease in overall land-use intensity, especially regarding fertilization intensity and mowing frequency. Thus, we conclude that, due to the great relevance of land-use intensity for most grassland ecosystem services, strategies and policies to support ecosystem-service multifunctionality need to regulate land-use intensity and–at the same time–need to account for resulting trade-offs such as the inevitable reduction in provisioning ecosystem services under extensive management. Overcoming these trade-offs should receive further attention in future research and practice. Because our study was focused on temperate grassland, future research should also assess management effects on the ecosystem-service multifunctionality of natural grasslands such as Savannas and prairies.

Building on plot-level assessments of management effects, such as the one carried out in the present research, investigating landscape-scale ecosystem-service multifunctionality considering both landscape composition and configuration, while suggesting new or alternative ways to manage grasslands (e.g., increasing the plant diversity of swards 12 ), could have the potential to additionally benefit the portfolio of ecosystem services provided by agricultural landscapes. Meanwhile, our plot-level results clearly suggest that diversifying grassland management where this is currently rather homogeneous across farms and landscapes would be an important and effective first step to increase ecosystem-service multifunctionality for sustainable grassland systems.

This research complies with all relevant ethical regulations and ETH Zürich’s legal service approved data collection, use and storage. The latter was also part of the declaration of consent that was signed by the farmers providing information on their grassland management.

Study area, local management practices, and sites

Measurements were carried out on permanent grassland, i.e., grassland not included in any crop rotation, in the Swiss Canton of Solothurn. This region presents a wide range of environmental conditions and stretches from the intensively managed Swiss lowlands (400–500 m a.s.l) in the South to the undulating Jura mountains (up to 1445 m a.s.l.). Agriculture in the canton is characterized by a high share of permanent grasslands (50% of the agriculturally used area 66 ), with comparably small parcels (average 0.9 ha 53 ) and farms (on average 23 ha) slightly higher than the national average (20.86 ha 67 ).

On organically managed grasslands, the use of mineral fertilizers and synthetic pesticides is forbidden. In Switzerland, the maximum allowed amount of organic fertilizers applied per year and hectare is somewhat lower than for non-organic grassland farming (135 vs. 162 kg available N for all intensive (non-Eco-scheme) grasslands of a farm at low elevations 68 ). As organic management is a farm-wide scheme and further guidelines exist, amongst others, regarding mowing and hay processing techniques, animal feed, fertilizer trade among farms, and access of livestock to outdoor areas 68 . In the Canton of Solothurn, 18% of grassland area is managed organically 66 . The studied Eco-schemes depicts an agri-environmental scheme requiring extensive grassland management with at least one harvest every year either by cutting (extensive meadows) or grazing (extensive pastures). Extensive management refers mainly to the ban of fertilization but can also include further regulations such as a delayed first date of cutting of meadows. In Switzerland, as part of the cross-compliance requirements for the eligibility to direct payments, a minimum of 7% of the utilized agricultural area of the farm must be dedicated to Eco-schemes but farmers can voluntarily register additional land beyond this minimum share. Extensively managed grasslands do not receive any fertilizer. Extensive meadows are further allowed to be mown only starting from a defined date (i.e., mid-June in lowland regions). In the Canton of Solothurn, our study area, extensively managed grasslands comprise 33% of the total permanent grassland area 66 . For the Harvest type, we chose the two dominant grassland types occurring in Central Europe. While meadows are predominately mown, with some occasional grazing such as at the end of the growing season, pastures are mainly grazed and rarely cut. This differentiation follows the official typology for Swiss grasslands and was confirmed by farmer interviews (Supplementary Table  S1 ).

Grassland plots were selected as described in the Supplementary material (Supplementary Methods). The result was a set of 86 grassland parcels, belonging to 36 farms (18 organic and 18 non-organic) across the Canton, spanning an elevational gradient from 435 to 1145 m a.s.l. (see also Supplementary Fig.  S1 for an overview of the number of farms and plots per eco-region of the Canton, and Supplementary Table  S1 for the number of plots included for each single combination of management aspects).

Several environmental factors were measured to account for potentially confounding effects of the local environment. Sand content and pH was measured from the soil samples taken in June 2020. Soil fractions were measured with a SP 2000 Robotic Clay Fraction Analyzer (Skalar Analytical B.V), and soil pH was measured potentiometrically from a water suspension of soil. The elevation of the plots was derived from a Digital Elevation Model (DEM) of the Copernicus Land Monitoring Service of the European Environment Agency 69 at a resolution of 25 m. From the DEM, northness, representing the orientation of the raster cell to the north, with +1 indicating north, and −1 south, was calculated. In QGIS.org, aspect of the land is in radians, and subsequently the cosine of this grid was computed to provide the northness. The inclination of each plot was assessed using the cell phone appliance Clinometer plaincode TM .

Management interviews with farmers

A questionnaire survey was conducted with farmers in January/February 2021 and 2022 in order to collect detailed information on the management of each investigated grassland plot. The information included grazing dates, number, age, and type of animals, as well as timing, amounts and nature of fertilizer applications. The grazing information was used to calculate the average livestock unit days ha −1 year −1 for each plot over the 2 years. From the information about amount and type of fertilizer, the total plant-available fertilizer N ha −1 year −1 was calculated based on information from ref. 70 about available N contents of the different organic fertilizers. Mineral fertilizer N was set to 100% available. The interviews also included questions about weed control measures (pesticide or mechanical; Supplementary Table  S1 ).

Measuring ecosystem-service indicators

In 2020 and 2021, intensive field and lab work were carried out to measure the 22 ecosystem-service indicators (Fig.  1 ), presenting twelve ecosystem services according to the CICES typology 29 . Regarding the measurement of ecosystem-service indicators, only the most relevant information is given here. Further details on these measurements and related analyses can be found in Supplementary Methods. The respective units of the measured ecosystem-service indicators are given in Supplementary Table  S3 .

In June 2020, a first soil sampling campaign was conducted to measure heavy metals, organic carbon stocks, microbial biomass carbon, and to determine the proportions of fungal guilds. Per plot, 20 soil samples along two 20 m transects were taken to a depth of 20 cm and pooled for subsequent analysis. Copper and zinc concentrations were analyzed from 2-mm sieved and air-dried soil using ICP-OS (5110 VDV ICP-OS, Agilent, Santa Clara, CA, US), divided by the respective reference values for Swiss soils, and the highest value of the two metal concentrations per plot was used for the ecosystem-service indicator heavy metals. Soil organic carbon was measured via sulfo-chromic oxidation 71 , and carbon stocks were calculated by multiplying organic carbon concentration with bulk density from 5 to 10 cm, which was measured as described below. Microbial biomass carbon was determined via chloroform fumigation 72 , 73 . For determination of the proportion of fungal guilds, specifically proportion of arbuscular mycorrhizal fungi (AMF) DNA, plant pathogenic fungi, and iconic fungi, DNA extracted from the soil samples was used for sequencing the fungal ITS region on an Illumina platform (Illumina, San Diego, CA, USA). DNA extraction, sequencing and bioinformatic processing was performed following ref. 74 , but see Supplementary Methods for details. Information about fungal guild membership of fungal taxa was identified using FunGUILD 75 for AM fungi and plant pathogenic fungi. Taxa belonging to CHEGD taxa, which include the often particularly colorful grassland macrofungi of high conservational value 76 , were identified as indicator for iconic fungi.

In August and September 2020, a second soil sampling campaign was carried out to measure root biomass, bulk density for soil compaction, and soil surface phosphorus concentrations. Root biomass was assessed by washing and sieving soil cores from 0 to 5 cm depth, from three pooled samples per parcel. To determine bulk density, the fine soil stock (FSS, g cm 3 ) was calculated according to ref. 77 and used together with clay content to calculate packing density 78 as a measure for soil compaction, which is closely related to infiltration capacity, using three pooled soil samples from 5 to 10 cm depth per plot. For surface soil phosphorus (P) concentrations, we used ten pooled shallow soil samples (1.5 cm deep) per plot, representing the stratum of soil P which is particularly at risk of erosion and thus depicts a potential eutrophication risk for freshwater ecosystems. Water-extractable soil phosphorus was measured photometrically (Evolution 220 with Cetac ASX-520, Thermo Fisher Scientific, Waltham, MA, USA).

Between the beginning of May and mid-June 2021, vegetation and earthworm surveys were conducted. For vascular plant species richness, all plant species occurring at two 2 m × 2 m quadrats (20 m apart from each other, each 10 m from the plot center) were recorded and summed for a total richness in plant species. The number of edible plant species was calculated based on the vegetation survey (the two 2 m × 2 m quadrats) and literature information 79 , 80 , 81 . Potential nectar provision was estimated using the cover of plant species from the vegetation surveys and data on nectar provision per species from the literature 82 , 83 . The number of agricultural weed plants (or of dense patches for clonal plants) was recorded along two transects per site. Leaf damage by herbivorous arthropods was assessed by sampling leaves in the field; one legume, grass, and herb leaf each (if available), every 50 cm along two perpendicular 20 m transects. subsequent visual examination of damage, and percentage of damaged leaves was used as the ecosystem-service indicator. Aboveground plant biomass was sampled repeatedly on the plots. In pastures, grazing exclusion cages were installed prior to grazing, and biomass could be sampled at 2 cm above the surface. The biomass sample taken closest to the first date of use as indicated by the farmers in a management survey was analyzed for digestibility (i.e., digestible organic matter) via enzymatic digestion in rumen fluid according to ref. 84 . For aboveground biomass yield, vegetation biomass was sampled close to a reference date set to end of May (day of year, DOY, 146). As some plots were sampled later or earlier, either due to displacement of the grazing exclusion cages by cow activity or to logistic reasons, biomass was corrected for sampling date. To this end, biomass weight was divided by the temperature-degree sum until sampling date following the approach described in ref. 85 . Symbiotic N 2 fixation in biomass harvested close to DOY 146 was calculated based on the aboveground biomass as described above and by considering identity and cover of occurring legume species. N content of the legume species occurring on each plot was measured and used together with the modeled mass percent of the respective legume and the biomass yield measure to calculate an index for N fixation (Supplementary Methods). To assess earthworm abundances, three soil pits (30 × 30 × 30 cm) were dug out and the excavated material was checked manually, and number of earthworm individuals were counted.

Esthetic appreciation of the plant community was derived from standardized pictures of each plot taken prior to the vegetation surveys. An online survey asking people for their personal perception of the esthetic quality of the respective grassland plant community on a 5-point Likert scale from attractive to unattractive was set up with QuestionPro (QuestionPro Inc, Austin, TX, USA), and widely distributed over e-mail and social media, with finally 414 respondents. The mean esthetic rating per plot was used as a value of esthetic appreciation. N 2 O emissions were calculated according to the IPCC guidelines 86 , using fertilizer data from the management interviews and Switzerland-specific information on livestock 70 to estimate the amount of N excreted by grazing animals. Information on N inputs was also used to estimate potential nitrate leaching using a tool developed by the UK Environment Agency accounting for fertilizer N and animal excreta as sources for nitrate leaching 87 .

Data analyses

Data were analyzed on three levels. First, ecosystem-service indicators were analyzed using multivariate regression, which allowed to jointly model all 22 indicators without loss of information while considering the correlations among them (see ref. 88 for a discussion of advantages). To allow for direct comparisons among model terms, indicators were normalized to a common scale by dividing each of the 22 response variables by their maximum 87 , 89 . To attain a multivariate normal distribution of residuals, some of the indicators had to be log-transformed and indicators, for which small values were regarded to have positive benefits (e.g., nitrate leaching), were reversed by subtracting these indicators’ maximum value from their respective values (see Supplementary Methods for details on these transformations). Using general linear latent variable models (GLLVM 32 ), the response matrix of ecosystem-service indicators was then regressed on the management aspects, namely Production system (factor with two levels: organic, non-organic), Eco-scheme (yes, no), and Harvest type (pasture, meadow). All regressions implied a Gaussian link and two latent variables, as models with more than two latent variables did often not converge. Where models converged, more than two latent variables did not change the fixed estimates and their standard errors. “The latent variables can be thought of as ordination scores, capturing the main axes of covariation of responses after controlling for observed predictors” (adapted from ref. 32 ). We included a random factor “farm pair”, with a level each to include all plots within a pair, to account for the blocking structure regarding pairs of organic/non-organic farms in the sampling design. We also tested a random factor “farm”, with a level each to include all plots within a farm; however, this random variance was always estimated to be zero and the random “farm” term was omitted from all models. The most parsimonious model was identified in the following way: we first ran a simple model including only the main effects of the three management aspects. Then we used forward selection under the second-order Akaike Information Criterion (AICc) 90 to determine, which of the five environmental variables (pH, sand content, elevation, inclination, and northness; each transformed to standard deviation scale) resulted in a most parsimonious model. Then, we ran this resulting model including any of the two-way interactions between the three management aspects (see Supplementary Table  S2 ). It turned out that a model with main effects and three of the environmental variables was most parsimonious (AICc = −2271.3). Given this outcome, we present the main effects in the results section and the effects of the environmental variables in Supplementary Fig.  S2 .

Second, to gain insights on the drivers of the observed effects of the three management aspects on the ecosystem-service indicators, structural equation models (SEMs) were calculated in the package lavaan 91 . In a first step, the effects of the topographic variables, i.e., elevation, northness and inclination, were tested on Eco-scheme and Harvest type. This was done because topography might have influenced farmers’ decision on how to manage the grassland. This was, however, not necessary for Production system, as meaningful differences in this factor had been eliminated due to plot selection (the blocking factor) in the sampling design. In a second step, the effect of the management aspects was tested on the three key measures of grassland management related to land-use intensity 31 : fertilizer N (available N: sum of organic and synthetic fertilizer, kg ha −1 year −1 ), number of cuts (year −1 ), and grazing intensity (livestock units days ha −1 year −1 ), derived from the management interviews. In a third step, the direct effect paths from the three management aspects to an ecosystem-service indicator as well as indirect effect paths via the three management intensity variables were tested. The model structure is shown in Fig.  4a ; the model was calculated separately for each indicator showing any statistically significant effect of management aspects in the GLLVM model.

Third, to assess the effect of the different management aspects on overall plot-scale multifunctionality, we used the approach suggested by Suter et al. 92 , which is based on the mean log response ratio (LRR) across ecosystem-service indicators for a given treatment comparison (e.g., organic vs. non-organic). In the context of multifunctionality, LRRs are a very useful measure because they are dimensionless effect sizes comparable among ecosystem services, can be calculated for different conditions (as in meta-analyses), and have particularly desirable statistical properties 93 . Moreover, the mean of several ecosystem-service indicators’ LRR (MLLR) between any two types of management (e.g., Eco-scheme yes versus no) has an intuitive meaning in that a greater number of indicators with higher LRRs reflect enhanced overall performance and therefore greater multifunctionality of one management type compared to another. Finally, the Euler’s number e raised to the power of the MLRR gives an overall effect size on the linear scale.

We preferred the MLRR as a measure of multifunctionality 92 over the most widely used averaging approach, where ecosystem-service indicators are averaged to result in one value of ecosystem-service multifunctionality per plot. This preference was motivated by at least two reasons. The first relates to interpretability. While the MLRR can be interpreted as an overall effect size derived from distinctly interpretable LRRs (similar to meta-analysis), a simple average of ecosystem-service indicators has little general meaning, even when individual variables are adjusted to a common scale. This is because variables with very different units and distributions are pooled (for example: masses, contents, counts, some of which typically have non-normal distributions), making it difficult to interpret such an index. In particular, effect sizes derived from such indices cannot be interpreted reasonably. The second reason for choosing the MLRR is that it allows for a transparent assessment of the contribution of each ecosystem service to the overall mean (compare Fig.  5 ). In contrast, the averaging approach comes with a loss of information, as ecosystem-service indicators can have (equal) opposite values or equivalent values, yet both cases will result in the same average metric. The impact of individual ecosystem-service indicators on such an average is generally not assessable. Finally, with our approach of using the MLLR, we follow recent demands to focus on effect sizes and their confidence intervals, rather than means and null-hypothesis significance testing 94 See also ref. 88 for a discussion of different multifunctionality metrics.

Here, given the outcome of the GLLVM, LRRs were calculated comparing organic versus non-organic, Eco-scheme yes versus no, and pasture versus meadow. As the main effects of the three management aspects did not or only marginally change, when the environmental variables were added to the model (compare Fig.  3 and Supplementary Fig.  S4 ), we avoided integrating these to the calculation of the MLRR. In particular, we refrain of using residuals from an initial regression of ecosystem-service indicators on the environmental variables to control for potential confounding because this procedure leads to biased model estimates 95 . For the calculation of the MLRR, LRRs of ecosystem-service indicators for which small values were regarded to have positive benefits were multiplied by −1. Then, the LRRs of indicators contributing to the same CICES-ecosystem service were averaged across the 12 CICES-ecosystem services (Fig.  1 ) and the MLRR was then calculated as the mean across the LRRs per CICES-ecosystem service. In doing so, ecosystem-service indicators informing about different aspects of one ecosystem service were downweighted to avoid over-representation of one CICES-ecosystem service over the others. Note that the aggregation of ecosystem-service indicators to a CICES-ecosystem service is equivalent to taking the average across all LRRs and weighting indicators by 1 divided by the number of respective indicators per CICES-ecosystem service. We chose to use the CICES framework as it is widely used in science and practice and thus allows for a better comparability of the results to other work. The MLRR was calculated across all CICES-ecosystem services and for each of the three ecosystem-service categories “provisioning”, “supporting/regulating”, and “cultural” to highlight potential trade-offs in the overall performance of management aspects. Finally, the 95% confidence interval to the MLRR was calculated by bootstrapping 96 (see Supplementary Methods and the Supplementary Code for details to averaging of LRRs across CICES-ecosystem services and the bootstrapping). All analyses were done using the statistical software R, version 4.2.0 97 and the package gllvm 32 . Further details concerning the statistical analyses can be found in Supplementary Methods. To support our results on overall multifunctionality based on the MLRR, we evaluated the effects of the management aspects (organic vs. non-organic, Eco-scheme extensive yes vs. no, and pasture vs. meadow) on multifunctionality using two further methods. First, we calculated a mean multifunctionality index using the estimates of the GLLVM as shown in Fig.  3 , and second, we calculated multifunctionality using the averaging approach. Using these two alternative approaches, we found the multifunctionality results to be highly similar to the MLRR. Based on these similar outcomes from two alternative methods, we conclude that our results for the MLRR are not only well interpretable but also highly reliable.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

The ecosystem-service indicator, environmental, and management data generated in this study have been deposited in the ETH research collection under accession code ethz-b-000663689 . The sequencing data is deposited in the European Nucleotide Archive under the accession number PRJEB72428 . Further databases used in this study: Unite v.83 database (Kõljalg et al. 98 ), FUNGuild database (Nguyen et al. 75 , Data on Nectar availability from Baude et al. 82 and Filipiak et al. 83 . The digital elevation model used is from the European Union (2018) Copernicus Land Monitoring Service, European Environment Agency (EEA) [ https://doi.org/10.5270/ESA-c5d3d65 ] (accessed 12.25.20).  Source data are provided with this paper.

Code availability

R Codes used for data preparation, to run the GLLVM, the SEMs, and the bootstrapping procedure for the confidence intervals to the MLRR is provided in the Supplementary Material. For all other analyses, available R packages were used.

Pe’er, G. et al. A greener path for the EU Common Agricultural Policy. Science 365 , 449–451 (2019).

Article   ADS   PubMed   Google Scholar  

Swinton, S. M., Lupi, F., Robertson, G. P. & Hamilton, S. K. Ecosystem services and agriculture: cultivating agricultural ecosystems for diverse benefits. Ecol. Econ. 64 , 245–252 (2007).

Article   Google Scholar  

Pe’er, G. et al. EU agricultural reform fails on biodiversity. Science 344 , 1090–1092 (2014).

White, R. P., Murray, S. & Rohweder, M. Pilot Analysis of Global Ecosystems—Grassland Ecosystems (World Resources Institute, Washington D.C., 2000).

Roser, M., Ritchie, H. & Rosado, P. Food supply. OurWorldInData.org. Retrieved from: https://ourworldindata.org/food-supply (2013).

FAO (Food and Agriculture Organization of the United Nations). Land, Inputs and Sustainability - Land Use. https://www.fao.org/faostat/en/#compare (2022).

FAOSTAT Food balances http://www.fao.org/faostat/en/#data/FBS (2023).

van Zanten, H. H. E., Meerburg, B. G., Bikker, P., Herrero, M. & de Boer, I. J. M. Opinion paper: The role of livestock in a sustainable diet: a land-use perspective. Animal 10 , 547–549 (2016).

Article   PubMed   Google Scholar  

MA (Millennium Ecosystem Assessment Board). Ecosystems and Human Well-Being—Health Synthesis . Business (Millennium Ecosystem Assessment, 2005).

Bengtsson, J. et al. Grasslands—more important for ecosystem services than you might think. Ecosphere 10 , 1–20 (2019).

Manning, P. et al. Redefining ecosystem multifunctionality. Nat. Ecol. Evol. 2 , 427–436 (2018).

Schils, R. L. M. et al. Permanent grasslands in Europe: land use change and intensification decrease their multifunctionality. Agric. Ecosyst. Environ . 330 , 107891 (2022).

Paudel, S. et al. A framework for sustainable management of ecosystem services and disservices in perennial grassland agroecosystems. Ecosphere 12 , e03837 (2021).

Allan, E. et al. Land use intensification alters ecosystem multifunctionality via loss of biodiversity and changes to functional composition. Ecol. Lett. 18 , 834–843 (2015).

Article   PubMed   PubMed Central   Google Scholar  

Neyret, M. et al. Assessing the impact of grassland management on landscape multifunctionality. Ecosyst. Serv. 52 , 101366 (2021).

Neyret, M. et al. Landscape management strategies for multifunctionality and social equity. Nat. Sustain. 6 , 391–403 (2023).

European Union. Farm to Fork Stragy for a Fair, Healthy and Environmentally-Friendly Food System (Communication from the EU Commission, COM, 2020).

FAO (Food and Agriculture Organization of the United Nations). Organic Agriculture, Report from the 15th Session of the Committee on Agriculture . http://www.fao.org/3/X0075e/X0075e.htm (1999).

Klaus, V. H., Richter, F., Buchmann, N., El Benni, N. & Lüscher, A. Effects of organic farming on ecosystem services and multifunctionality in Switzerland: the ServiceGrass project. Grassl. Sci. Eur. 25 , 505–507 (2020).

Google Scholar  

Wittwer, R. A. et al. Organic and conservation agriculture promote ecosystem multifunctionality. Sci. Adv. 7 , 1–13 (2021).

Seufert, V., Ramankutty, N. & Foley, J. A. Comparing the yields of organic and conventional agriculture. Nature 485 , 229–232 (2012).

Article   ADS   CAS   PubMed   Google Scholar  

Blumentrath, C., Stokstad, G., Dramstad, W. & Eiter, S. Agri-Environmental Policies and Their Effectiveness in Norway, Austria, Bavaria, France, Switzerland and Wales: Review and Recommendations . Skog og Landskap Rapport 11/2014 (Norsk institutt for skog og landskap, 2014).

Batáry, P. et al. 2015 - The role of agri-environment schemes in conservation and environmental management. Conserv. Biol. 29 , 1006–1016 (2021).

Elmiger, N., Finger, R., Ghazoul, J. & Schaub, S. Biodiversity indicators for result-based agri-environmental schemes—current state and future prospects. Agric. Syst. 204 , 103538 (2023).

Pauler, C. M. et al. Choosy grazers: influence of plant traits on forage selection by three cattle breeds. Funct. Ecol. 34 , 980–992 (2020).

Silva, V. et al. Effects of grazing on plant composition, conservation status and ecosystem services of Natura 2000 shrub-grassland habitat types. Biodivers. Conserv. 28 , 1205–1224 (2019).

Grigulis, K. et al. Relative contributions of plant traits and soil microbial properties to mountain grassland ecosystem services. J. Ecol. 101 , 47–57 (2013).

Hiltbrunner, D., Schulze, S., Hagedorn, F., Schmidt, M. W. I. & Zimmmermann, S. Cattle trampling alters soil properties and changes soil microbial communities in a Swiss sub-alpine pasture. Geoderma 170 , 369–377 (2012).

Article   ADS   CAS   Google Scholar  

Haines-Young, R. & Potschin, M. CICES V5. 1. Guidance on the Application of the Revised Structure (Fabis Consulting Ltd., 2018).

Richter, F. et al. A guide to assess and value ecosystem services of grasslands. Ecosyst. Serv. 52 , 101376 (2021).

Blüthgen, N. et al. A quantitative index of land-use intensity in grasslands: integating mowing, grazing and fertilization. Basic Appl. Ecol. 13 , 207–220 (2012).

Niku, J., Hui, F. K. C., Taskinen, S. & Warton, D. I. gllvm: fast analysis of multivariate abundance data with generalized linear latent variable models in r. Methods Ecol. Evol. 10 , 2173–2182 (2019).

Chmelíková, L., Schmid, H., Anke, S. & Hülsbergen, K. J. Nitrogen-use efficiency of organic and conventional arable and dairy farming systems in Germany. Nutr. Cycl. Agroecosyst. 119 , 337–354 (2021).

Klaus, V. H. et al. Does organic grassland farming benefit plant and arthropod diversity at the expense of yield and soil fertility? Agric. Ecosyst. Environ. 177 , 1–9 (2013).

Fan, F., Henriksen, C. B. & Porter, J. Long-term effects of conversion to organic farming on ecosystem services - a model simulation case study and on-farm case study in Denmark. Agroecol. Sustain. Food Syst. 42 , 504–529 (2018).

Sandhu, H. S., Wratten, S. D. & Cullen, R. The role of supporting ecosystem services in conventional and organic arable farmland. Ecol. Complex. 7 , 302–310 (2010).

Williams, A. & Hedlund, K. Indicators of soil ecosystem services in conventional and organic arable fields along a gradient of landscape heterogeneity in southern Sweden. Appl. Soil Ecol. 65 , 1–7 (2013).

Schneider, M. K. et al. Gains to species diversity in organically farmed fields are not propagated at the farm level. Nat. Commun. 5 , 4151 (2014).

Einarsson, R. et al. Crop production and nitrogen use in European cropland and grassland 1961–2019. Sci. Data 8 , 1–29 (2021).

Herzog, F. et al. Assessing the intensity of temperate European agriculture at the landscape scale. Eur. J. Agron. 24 , 165–181 (2006).

van Dobben, H. F., Quik, C., Wamelink, G. W. W. & Lantinga, E. A. Vegetation composition of Lolium perenne-dominated grasslands under organic and conventional farming. Basic Appl. Ecol. 36 , 45–53 (2019).

Le Provost, G. et al. The supply of multiple ecosystem services requires biodiversity across spatial scales. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-022-01918-5 (2022).

Babur, E. et al. Nitrogen fertilizer effects on microbial respiration, microbial biomass, and carbon sequestration in a Mediterranean Grassland Ecosystem. Int. J. Environ. Res. 15 , 655–665 (2021).

Article   CAS   Google Scholar  

Dietrich, P., Buchmann, T., Cesarz, S., Eisenhauer, N. & Roscher, C. Fertilization, soil and plant community characteristics determine soil microbial activity in managed temperate grasslands. Plant Soil 419 , 189–199 (2017).

Hoeffner, K. et al. Soil properties, grassland management, and landscape diversity drive the assembly of earthworm communities in temperate grasslands. Pedosphere 31 , 375–383 (2021).

Gossner, M. M., Weisser, W. W. & Meyer, S. T. Invertebrate herbivory decreases along a gradient of increasing land-use intensity in German grasslands. Basic Appl. Ecol. 15 , 347–352 (2014).

Klaus, V. H. et al. Additive effects of two agri-environmental schemes on plant diversity but not on productivity indicators in permanent grasslands in Switzerland. J. Environ. Manag. 348 , 119416 (2023).

Knop, E., Kleijn, D., Herzog, F. & Schmid, B. Effectiveness of the Swiss agri-environment scheme in promoting biodiversity. J. Appl. Ecol. 43 , 120–127 (2006).

Leroy, G., Hoffmann, I., From, T., Hiemstra, S. J. & Gandini, G. Perception of livestock ecosystem services in grazing areas. Animal 12 , 2627–2638 (2018).

Article   CAS   PubMed   Google Scholar  

Barry, S. J. Using social media to discover public values, interests, and perceptions about cattle grazing on park lands. Environ. Manag. 53 , 454–464 (2014).

Article   ADS   Google Scholar  

Bradford, M. A. et al. Discontinuity in the responses of ecosystem processes and multifunctionality to altered soil community composition. Proc. Natl. Acad. Sci. USA 111 , 14478–14483 (2014).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Byrnes, J. E. K. et al. Investigating the relationship between biodiversity and ecosystem multifunctionality: challenges and solutions. Methods Ecol. Evol. 5 , 111–124 (2014).

Le Clec’h, S. et al. Assessment of spatial variability of multiple ecosystem services in grasslands of different intensities. J. Environ. Manag. 251 , 109372 (2019).

Savage, J. et al. Management to support multiple ecosystem services from productive grasslands. Sustain 13 , 1–15 (2021).

Tälle, M. et al. Grazing vs. mowing: A meta-analysis of biodiversity benefits for grassland management. Agric. Ecosyst. Environ. 222 , 200–212 (2016).

Busch, V. et al. Will I stay or will I go? Plant species-specific response and tolerance to high land-use intensity in temperate grassland ecosystems. J. Veg. Sci. 30 , 674–686 (2019).

Mayel, S., Jarrah, M. & Kuka, K. How does grassland management affect physical and biochemical properties of temperate grassland soils? A review study. Grass Forage Sci. 76 , 215–244 (2021).

Schlaghamerský, J., Šídová, A. & Pižl, V. From mowing to grazing: does the change in grassland management affect soil annelid assemblages? Eur. J. Soil Biol. 43 , S72–S78 (2007).

Bilotta, G. S., Brazier, R. E. & Haygarth, P. M. The Impacts of Grazing Animals on the Quality of Soils, Vegetation, and Surface Waters in Intensively Managed Grasslands . Advances in Agronomy , Vol. 94 (Elsevier Masson SAS, 2007).

Linders, T. E. W. et al. Stakeholder priorities determine the impact of an alien tree invasion on ecosystem multifunctionality. People Nat. 3 , 658–672 (2021).

Peter, S., Le Provost, G., Mehring, M., Müller, T. & Manning, P. Cultural worldviews consistently explain bundles of ecosystem service prioritisation across rural Germany. People Nat. 4 , 218–230 (2022).

Knudsen, M. T. et al. The importance of including soil carbon changes, ecotoxicity and biodiversity impacts in environmental life cycle assessments of organic and conventional milk in Western Europe. J. Clean. Prod. 215 , 433–443 (2019).

Mack, G., Ritzel, C. & Jan, P. Determinants for the implementation of action-, result- and multi-actor-oriented agri-environment schemes in Switzerland. Ecol. Econ. 176 , 106715 (2020).

Kampmann, D. et al. Mountain grassland biodiversity: impact of site conditions versus management type. J. Nat. Conserv. 16 , 12–25 (2008).

Stumpf, F. et al. Spatial monitoring of grassland management using multi-temporal satellite imagery. Ecol. Indic. 113 , 106201 (2020).

GELAN. Agrarinformationssystem GELAN, Amt für Landwirtschaft und Natur. Zollikofen, Switzerland. http://www.gelan.ch/de/ (2019).

FSO (Federal STatistical Office). Landwirtschaftsbetriebe, Beschäftigte, Nutzfläche Nach Kanton . (Federal STatistical Office, 2023).

Bio Suisse. Richtlinien Für Die Erzeugung, Verarbeitung Und Den Handelvon Knospe-Produkten . (Bio Suisse, 2023).

European Union. Copernicus Land Monitoring Service, European Environment Agency (EEA). https://doi.org/10.5270/ESA-c5d3d65 (2018).

Richner, W., Flisch, R., Mayer, J. & Schlegel, P. 4/Eigenschaften und Anwendung von Düngern. Grundlagen für die Düngung landwirtschaftlicher Kulturen in der Schweiz/GRUD 8 , 1–24 (2017).

Walkley, A. & Black, I. A. An examination of the degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci. 37 , 29–38 (1934).

Schinner, F. & Sonnleitner, R. Methoden der Bodenmikrobiologie und -biochemie. Bodenökologie: Mikrobiologie und Bodenenzymatik Band https://doi.org/10.1007/978-3-642-80175-4_4 (1996).

Vance, E. D., Brookes, P. C. & Jenkinson, D. S. An extraction method for measuring soil microbial biomass C. Soil Biol. Biochem. 19 , 703–707 (1987).

Longepierre, M. et al. Mixed effects of soil compaction on the nitrogen cycle under pea and wheat. Front. Microbiol. 12 , 1–16 (2022).

Nguyen, N. H. et al. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20 , 241–248 (2016).

Caboň, M. et al. Mulching has negative impact on fungal and plant diversity in Slovak oligotrophic grasslands. Basic Appl. Ecol. 52 , 24–37 (2021).

Poeplau, C., Vos, C. & Don, A. Soil organic carbon stocks are systematically overestimated by misuse of the parameters bulk density and stone content. SOIL Discuss 3 , 61–66 (2017).

CAS   Google Scholar  

Renger, M. Über den Einfluss der Dränung auf das Gefüge und die Wasserdurchlässigkeit bindiger Böden. Mitteilungen Dtsch. Bodenkundliche Ges. 11 , 23–28 (1970).

Pfister, T. & auf der Mauer, F. Aromatische Bergkräuter Für Die Naturküche Sammeln Und Zubereiten (Haupt Verlag, 2017).

Machatschek, M. & Mautner, E. Speisekammer Aus Der Natur Bevorratung Und Haltbarmachung von Wildpflanzen (Böhlau Verlag, 2015).

Höller, A. & Grappendorf, D. Essbare Wildsamen Finden, Sammeln Und Geniessen (Ulmer Verlag, 2019).

Baude, M. et al. Historical nectar assessment reveals the fall and rise of floral resources in Britain. Nature 530 , 85–88 (2016).

Filipiak, M., Walczyńska, A., Denisow, B., Petanidou, T. & Ziółkowska, E. Phenology and production of pollen, nectar, and sugar in 1612 plant species from various environments. Ecology 103 , 2021–2022 (2022).

Tilley, J. M. A. & Terry, R. A. A two-stage technique for the in vitro digestion of forage crops. Grass Forage Sci. 18 , 104–111 (1963).

Menzi, H., Blum, H. & Nössberger, J. Relationship between climatic factors and the dry matter production of swards of different composition at two altitudes. Grass Forage Sci. 46 , 223–230 (1991).

IPCC. N2O emissions from managed soils, and CO2 emissions from lime and urea application. In 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2019).

Martin, I., Davison, P. & Bramer, S. The Nitrate Leaching Tool - Technical Reference (UK Environment Agency, 2021).

Dooley, Á. et al. Testing the effects of diversity on ecosystem multifunctionality using a multivariate model. Ecol. Lett. 18 , 1242–1251 (2015).

Gamfeldt, L. & Roger, F. Revisiting the biodiversity-ecosystem multifunctionality relationship. Nat. Ecol. Evol. 1 , 1–7 (2017).

Anderson, D. R. & Burnham, K. P. Avoiding pitfalls when using information-theoretic methods. J. Wildl. Manag. 66 , 912–918 (2002).

Rosseel, Y. lavaan: an R package for structural equation modeling. J. Stat. Softw. 48 , 1–36 (2012).

Suter, M., Huguenin-Elie, O. & Lüscher, A. Multispecies for multifunctions: combining four complementary species enhances multifunctionality of sown grassland. Sci. Rep. 11 , 1–16 (2021).

Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80 , 1150–1156 (1999).

Ho, J., Tumkaya, T., Aryal, S., Choi, H. & Claridge-Chang, A. Moving beyond P values: data analysis with estimation graphics. Nat. Methods 16 , 565–566 (2019).

Freckleton, R. P. On the misuse of residuals in ecology: regression of residuals vs. multiple regression. J. Anim. Ecol. 71 , 542–545 (2002).

Davison, A. C. & Hinkley, D. V. Bootstrap Methods and Their Application (Cambridge University Press, Cambridge, 1997).

R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, Austria, 2021).

Kõljalg, U. et al. The Taxon Hypothesis Paradigm—on the unambiguous detection and communication of taxa. Microorganisms 8 , 1910 (2020).

Download references

Acknowledgements

The authors thank the farmers of the grasslands, all persons involved in field and lab work, especially Eliana Mohn, Friederike Meyer and Jannis Weil, and all people involved in project administration (Anna Gilgen) and scientific discussions, especially Olivier Huguenin-Elie, Peter Manning, Sara D. Leonhardt, Solen Le Clec'h and Eric Allan. We acknowledge funding from the Mercator Foundation Switzerland (15398; V.H.K., A.L., and N.E.-B.), the Foundation Sur-la-Croix (V.H.K. and A.L., no grant number), and the Pancivis Foundation (PAN 2019/31; V.H.K. and M.H.). Finally, we thank the anonymous reviewers whose feedback improved this work.

Open access funding provided by Swiss Federal Institute of Technology Zurich.

Author information

Authors and affiliations.

Grassland Sciences, Institute of Agricultural Sciences, ETH Zürich, Zürich, Switzerland

Franziska J. Richter, Nina Buchmann & Valentin H. Klaus

Forage Production and Grassland Systems, Agroscope, Zürich, Switzerland

Matthias Suter, Andreas Lüscher & Valentin H. Klaus

Sustainability Assessment and Agricultural Management, Agroscope, Ettenhausen, Switzerland

Nadja El Benni

Sustainable Agroecosystems, Institute of Agricultural Sciences, ETH Zürich, Zürich, Switzerland

Rafaela Feola Conz & Martin Hartmann

Managerial Economics in Agriculture, Agroscope, Ettenhausen, Switzerland

Pierrick Jan

You can also search for this author in PubMed   Google Scholar

Contributions

V.H.K. and A.L. conceived the idea and developed the project with inputs from F.J.R. and N.B.; F.J.R. was responsible for data generation with input and support by M.H., R.F.-C. and V.H.K.; F.J.R. and M.S. analyzed the data with input from V.H.K.; F.J.R. wrote the manuscript, led by V.H.K. and M.S., to which N.B., N.E.-B., P.J., A.L., M.H. and R.F.-C. contributed advice and comments, and gave final approval for publication.

Corresponding author

Correspondence to Franziska J. Richter .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Nature Communications thanks Jiangxiao Qiu, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary information, reporting summary, peer review file, source data, source data, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Richter, F.J., Suter, M., Lüscher, A. et al. Effects of management practices on the ecosystem-service multifunctionality of temperate grasslands. Nat Commun 15 , 3829 (2024). https://doi.org/10.1038/s41467-024-48049-y

Download citation

Received : 14 June 2023

Accepted : 19 April 2024

Published : 07 May 2024

DOI : https://doi.org/10.1038/s41467-024-48049-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

Advertisement

Ecosystem services valuation: a review of concepts, systems, new issues, and considerations about pollution in ecosystem services

• Review Article
• Published: 20 June 2023
• Volume 30 , pages 83051–83070, ( 2023 )

Cite this article

• Mehdi Zandebasiri 1 ,
• Hassan Jahanbazi Goujani 1 ,
• Yaghoub Iranmanesh 1 ,
• Hossein Azadi 2 ,
• Ants-Hannes Viira 3 &
• Mohsen Habibi 4  

1317 Accesses

4 Citations

1 Altmetric

Explore all metrics

Managers can determine the function of ecosystem services in decision-making processes through valuation. Ecological functions and processes that benefit people lead to ecosystem services. Valuing ecosystem services mean finding values for the benefits of ecosystem services. For the concepts related to ecosystem services and their valuation, categories in different articles have been presented. One of the most important issues is providing a suitable grouping for different methods and concepts of valuing ecosystem services. In this study, the most recent topics related to ecosystem service valuation methods were compiled and categorized by using the system theory. The aim of this study was to introduce some of the most important classical and modern methods and concepts of valuing ecosystem services. For this aim, a review of articles related to ecosystem service valuation methods, content analysis, and categorization of their contents was used to provide definitions, concepts, and categorization of different methods. To summarize, valuation methods are classified into two types: classical and modern methods. Classical approaches include the avoided cost method, the replacement cost method, the factor income method, the travel cost method, hedonic pricing, and contingent value. Modern methods include the basic value transfer method, deliberative ecosystem service valuation, valuation of climate change risks, and other cases that evolve every day in the world of science. Findings of the paper have the potential to be beneficial in comprehending the definitions and ideas of ecosystem services in ecosystem management, particularly in protected areas, participatory management, and pollutant research. This research can add to the worldwide literature on the valuing of ecosystem services while also determining the most pressing issues and difficulties of today, such as climate change, pollution, ecosystem management, and participatory management.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

The Research Unit RU 816: Overall Approach in the Light of the Ecosystem Services Concept

Economic Valuation of Ecosystem Services

The Basic Ideas of the Ecosystem Service Concept

Data availability.

For further information, please contact with the corresponding author: [email protected].

Alphayo IL, Lance W, Oliver RVW et al (2020) Economic valuation of grazing management practices: discrete choice modeling in pastoral systems of Kenya. J Environ Plan Manage 63(2):335–351. https://doi.org/10.1080/09640568.2019.1584097

Article   Google Scholar  

Amirnejad H, AtaeiSolout K (2017) Estimation of economic value of gas regulation function in Bemo National Park rangeland ecosystem (case study: stabilization of carbon dioxide and oxygen supply). J Environ Res 8(15):193–202 (In Persian)

Google Scholar  

Azadi H, Van Passel S, Cools J (2021) Rapid economic valuation of ecosystem services in man and biosphere reserves in Africa: a review. Global Ecol Conserv 28:e01697

Bernue’s A, Rodrı’guez-Ortega T, Ripoll-Bosch R, Alfnes F (2014) socio-cultural and economic valuation of ecosystem services provided by Mediterranean mountain agroecosystems. Plos One 9(7):e102479. https://doi.org/10.1371/journal.pone.0102479

Article   CAS   Google Scholar  

Byrne AT, Hadrich JC, Robinson E, Han G (2020) A factor-income approach to estimating grassland protection subsidy payments to livestock herders in Inner Mongolia China. Land Use Policy 91:104352. https://doi.org/10.1016/j.landusepol.2019.104352

Chen H (2021) The ecosystem service value of maintaining and expanding terrestrial protected areas in China. Sci Total Environ 781:146768. https://doi.org/10.1016/j.scitotenv.2021.146768

Chen H, Costanza R, Kubiszewski R (2022) Land use trade-offs in China’s protected areas from the perspective of accounting values of ecosystem services. J Environ Manage 315:115178. https://doi.org/10.1016/j.jenvman.2022.115178

Comte A, Campagne CS, Lange S et al (2022) Ecosystem accounting: Past scientific developments and future challenges. Ecosyst Serv 58:101486. https://doi.org/10.1016/j.ecoser.2022.101486

Costanza R (2020) Valuing natural capital and ecosystem services toward the goals of efficiency, fairness, and sustainability. Ecosyst Serv 43:101096. https://doi.org/10.1016/j.ecoser.2020.101096

Costanza R, de Groot R, Sutton PC et al (2014) Changes in the global value of ecosystem services. Global Environ Change 26:152–158. https://doi.org/10.1016/j.gloenvcha.2014.04.002

Costanza R, De Groot R, Braat L et al (2017) Twenty years of ecosystem services: how far have we come and how far do we still need to go? Ecosyst Serv 28:1–16. https://doi.org/10.1016/j.ecoser.2017.09.008

Costanza R, Anderson ShJ, Sutton P et al (2021) The global value of coastal wetlands for storm protection. Global Environ Change 70:102328. https://doi.org/10.1016/j.gloenvcha.2021.102328

Czembrowski P, Kronenberg J (2016) Hedonic pricing and different urban green space types and sizes: Insights into the discussion on valuing ecosystem services. Landsc Urban Plan 146:11–19. https://doi.org/10.1016/j.landurbplan.2015.10.005

Czúcza B, Haines-Young R, Kissa M et al (2020) Ecosystem service indicators along the cascade: how do assessment and mapping studies position their indicators? Ecol Indic 118(2020):106729. https://doi.org/10.1016/j.ecolind.2020.106729

Danehkar A, Zandebasiri M (2020) System analysis in environment. University of Tehran Press. (In Persian)

de Groot RS, Wilson M, Boumans R (2002) A typology for the description, classification and valuation of ecosystem functions, goods and services. Ecol Econ 41(3):393–408

DEWHA (Department of the Environment, Water, Heritage and the Arts), (2009). Ecosystem services: key concepts and applications, Occasional Paper No 1, Department of the Environment, Water, Heritage and the Arts, Canberra. Available at: https://www.awe.gov.au/sites/default/files/documents/ecosystem-services.pdf

ELD (Economics of Land Degradation) Initiative (2019). ELD Campus. Module: valuation of ecosystem services. 40 P. Available from www.eld-initiative.org .

Farber S, Costanza R, Wilson MA (2002) Economic and ecological concepts for valuing ecosystem services. Ecol Econ 41:375–392

Farber S, Costanza R, Childers DL et al (2006) Linking ecology and economics for ecosystem management. Bioscience 56:121–133. https://doi.org/10.1641/0006-3568(2006)056[0121:LEAEFE]2.0.CO;2

Goel P (2006) Water pollution: causes, effects and control. New Age International

Haines‐Young R and Potschin M (2014) Typology/classification of ecosystem services. In: Potschin, M. and K. Jax (eds): OpenNESS Ecosystem services reference book. EC FP7 Grant Agreement no. 308428. Available via: http://www.openness-project.eu/library/reference-book

Hassen A, Zander KK, Manes S, Meragiaw M (2023) Local People’s perception of forest ecosystem services, traditional conservation, and management approaches in North Wollo Ethiopi. J Environ Manage 330:117118. https://doi.org/10.1016/j.jenvman.2022.117118

Herd-Hoare S, Shackleton CM (2020) Ecosystem disservices matter when valuing ecosystem benefits from small-scale arable agriculture. Ecosyst Serv 46:101201. https://doi.org/10.1016/j.ecoser.2020.101201

Himes-Cornell A, Pendleton L, Atiyah P (2018) Valuing ecosystem services from blue forests: a systematic review of the valuation of salt marshes, sea grass beds and mangrove forests. Ecosyst Serv 30(Part A):36–48. https://doi.org/10.1016/j.ecoser.2018.01.006

Iranmanesh Y, Pourhashemi M, Jahanbazi H et al (2022) Study of traditional and formal knowledge of acorn harvesting of brant`s oak (Quercus brantii Lindl.) trees in the Zagros forests. Ecol Iranian For 9(18):81–93 (In Persian with English abstract)

Jones MLM, Provins A, Harper-Simmonds L, et al. (2012) Using the Ecosystems Services Approach to value air quality. Full technical report to Defra, project NE0117. Available via: https://ukair.defra.gov.uk/assets/documents/reports/cat10/1511251138_NE0117_Using_the_ecosystems_services_approach_to_value_air_quality.pdf

Jones L, Vieno M, Morton D, et al. (2017) Developing estimates for the valuation of air pollution removal in ecosystem accounts. Final report for Office of National Statistics, July 2017. Available via: https://nora.nerc.ac.uk/id/eprint/524081/7/N524081RE.pdf

Jackson S, Finn M, Scheepers K (2014) The use of replacement cost method to assess and manage the impacts of water resource development on Australian indigenous customary economies. J Environ Manage 135:100–109. https://doi.org/10.1016/j.jenvman.2014.01.018

Juutinen A, Immerzeel B, Pouta E et al (2022) A comparative analysis of the value of recreation in six contrasting Nordic landscapes using the travel cost method. J Outdoor Recreat Tour 39(2022):100528. https://doi.org/10.1016/j.jort.2022.100528

Kubiszewski I, Concollato L, Costanza R, Stern DI (2023) Changes in authorship, networks, and research topics in ecosystem services. Ecosyst Serv 59:101501. https://doi.org/10.1016/j.ecoser.2022.101501

Langle-Flores A, Quijas S (2020) A systematic review of ecosystem services of Islas Marietas National Park, Mexico, an insular marine protected area. Ecosyst Serv 46:101214. https://doi.org/10.1016/j.ecoser.2020.101214

Lefeuvre NB, Keller N, Plagnat-Contoreggi P et al (2022) The value of logged tropical forests: a study of ecosystem services in Sabah, Borneo. Environ Sci Policy 128:56–67. https://doi.org/10.1016/j.envsci.2021.11.003

Liebelt V, Bartke S, Schwarz N (2018) Hedonic pricing analysis of the influence of urban green spaces onto residential prices: the case of Leipzig Germany. Eur Plan Stud 26(1):133–157. https://doi.org/10.1080/09654313.2017.1376314

Liu Y, Zhou S, Chen Y et al (2022) How do local people value ecosystem service benefits receive from conservation programs? Evidence from nature reserves on the Hengduan Mountains. Global Ecol Conserv 33:e01979. https://doi.org/10.1016/j.gecco.2021.e01979

Ling MA, King S, Mapendembe A, Brown C (2018) A review of ecosystem service valuation progress and approaches by the Member States of the European Union. UNEPWCMC, Cambridge,UK. https://ec.europa.eu/environment/nature/capital_accounting/pdf/eu_es_valuation_review.pdf

Martínez-Jiménez ET, Pérez-Campuzano E, Ibarra AA (2017) Hedonic pricing model for the economic valuation of conservation land in Mexico City. Trans Ecol Environ 223:101–111. https://doi.org/10.2495/SC170091

Mashayekhi Z, Sharzehi GhA, Danehkar A, Majed V (2018) A comparison of stated preferences methods for economic valuation of ecosystem services (case study: Qeshm mangrove ecosystems). Environ Sci 16(1):69–88 (In Persian with English abstract)

Maynard S, James D, Davidson A (2015) Determining the value of multiple ecosystem services in terms of community wellbeing: who should be the valuing agent? Ecol Econ 115:22–28. https://doi.org/10.1016/j.ecolecon.2014.02.002

McPhearson T, Cook EM, Berbe’s-Bla’zquez M (2022) A social-ecological- echnological systems framework for urban ecosystem services. One earth 5(5):505–518. https://doi.org/10.1016/j.oneear.2022.04.007

Melgar-Melgar RE, Hall ChAS (2020) Why ecological economics needs to return to its roots: the biophysical foundation of socio-economic systems. Ecol Econ 169:106567. https://doi.org/10.1016/j.ecolecon.2019.106567

Melvani K, Myers TLB, Stacey N et al (2022) Farmers’ values for land, trees and biodiversity underlie agricultural sustainability. Land Use Policy 117:105688. https://doi.org/10.1016/j.landusepol.2021.105688

Ndebele T, Forgie V (2017) Estimating the economic benefits of a wetland restoration programme in New Zealand: a contingent valuation approach. Econ Anal Policy 55:75–89. https://doi.org/10.1016/j.eap.2017.05.002

Nesbitt L, Hotte N, Barron S et al (2017) The social and economic value of cultural ecosystem services provided by urban forests in North America: a review and suggestions for future research. Urban For Urban Green 25:103–111. https://doi.org/10.1016/j.ufug.2017.05.005

Ninan KN, Inoue M (2013) Valuing forest ecosystem services: case study of a forest reserve in Japan. Ecosyst Serv 5:e78–e87. https://doi.org/10.1016/j.ecoser.2013.02.006

Ninan KN, Kontolen A (2016) Valuing forest ecosystem services and disservices –case study of a protected area in India. Ecosyst Serv 20:1–14. https://doi.org/10.1016/j.ecoser.2016.05.001

Novikov DA (2015) Systems theory and systems analysis. systems engineering in cybernetics: from past to future. – Heidelberg: Springer, 107 p. https://link.springer.com/chapter/ https://doi.org/10.1007/978-3-319-27397-6_4

Potschin M, Haines-Young R (2011) Ecosystem services. Prog Phys Geogr 35(5):575–594

Potschin M and Haines-Young R (2016) Defining and measuring ecosystem services. In: Potschin M, Haines-Young R, Fish R, Turner RK (eds) Routledge Handbook of Ecosystem Services. Routledge, London and ä New York. https://doi.org/10.4324/9781315775302

Pourtoosi N, Koocheki A, Nasiri Mahalati M, Ghorbani M (2018) Economic valuation of the ecosystem services of Mashhad’s Parks. Environ Sci 15(4):155–176 (In Persian with English abstract)

Richter F, Jan P, Benni NEI et al (2021) A guide to assess and value ecosystem services of grasslands. Ecosyst Serv 52:101376. https://doi.org/10.1016/j.ecoser.2021.101376

Rising JM, Taylor Ch, Ives MC, Ward RET (2022) Challenges and innovations in the economic evaluation of the risks of climate change. Ecol Econ 197(2022):107437. https://doi.org/10.1016/j.ecolecon.2022.107437

Rolón E, José Rosso J, Mabragaña E et al (2022) Distribution and accumulation of major and trace elements in water, sediment, and fishes from protected areas of the Atlantic Rainforest. Environ Sci Pollut Res 29:58843–58868. https://doi.org/10.1007/s11356-022-19416-3

Sanchez JJ, Marcos-Martinez R, Srivastava L et al (2021) Valuing the impacts of forest disturbances on ecosystem services: an examination of recreation and climate regulation services in U.S. national forests. Trees For People 5:100123. https://doi.org/10.1016/j.tfp.2021.100123

Sangha KK, Russell-Smith J, Morrison SC (2017) Challenges for valuing ecosystem services from an indigenous estate in northern Australia. Ecosyst Serv 25:167–178. https://doi.org/10.1016/j.ecoser.2017.04.013

Schon NL, Dominati EJ (2020) Valuing earthworm contribution to ecosystem services delivery. Ecosyst Serv 43:101092. https://doi.org/10.1016/j.ecoser.2020.101092

Sharzei GhA, Majed V (2015) Using choice experiment to value Zarinehroud’s environmental functions improvement. Environ Sci 13(2):133–144 (In Persian with English abstract)

Shen X, Gatto P, Pagliacci F (2023) Unravelling the role of institutions in market-based instruments: a systematic review on forest carbon mechanisms. Forests 14:136. https://doi.org/10.3390/f14010136

Small N, Munday M, Durancec I (2017) The challenge of valuing ecosystem services that have no material benefits. Glob Environ Chang 44:57–67. https://doi.org/10.1016/j.gloenvcha.2017.03.005

Small A, Owne A, Paavola J (2021) Organizational use of ecosystem service approaches: a critique from a systems theory perspective. Bus Strat Environ: 1 –13. https://doi.org/10.1002/bse.2887

Smith N, Deal R, Kline J, et al. 2011 Ecosystem services as a framework for forest stewardship: Deschutes National Forest overview. Gen. Tech. Rep. PNW-GTR-852. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 46 p.

Stenger A, Harou P, Navrud S (2009) Valuing environmental goods and services derived from the forests. J for Econ 15:1–14. https://doi.org/10.1016/j.jfe.2008.03.001

Torrel LA, Torell GL, Skaggas RK (2014) Incorporating ecosystem services into economic assessments of restoration projects. Rangelands 36(2):45–51. https://doi.org/10.2111/RANGELANDS-D-13-00054.1

Torres-Ortega S, Pérez-Álvarez R, Díaz-Simal P et al (2018) Economic valuation of cultural heritage: application of travel cost method to the National Museum and Research Center of Altamira. Sustainability 2018(10):2550. https://doi.org/10.3390/su10072550

Turner H, Archer RA, Downey LE et al (2021) An introduction to the main types of economic evaluations used for informing priority setting and resource allocation in healthcare: key features, uses, and limitations. Front Public Health 9:722927. https://doi.org/10.3389/fpubh.2021.722927

Tyllianakis E, Callaway A, Vanstaen K, Luisetti T (2019) The value of information: Realising the economic benefits of mapping seagrass meadows in the British Virgin Islands. Sci Total Environ 650:2107–2116. https://doi.org/10.1016/j.scitotenv.2018.09.296

Van Houtven G, Mansfield C, Phaneuf DJ et al (2014) Combining expert elicitation and stated preference methods to value ecosystem services from improved lake water quality. Ecol Econ 99:40–52. https://doi.org/10.1016/j.ecolecon.2013.12.018

Van Opstal NV, Seehaus MS, Gabioud EA et al (2022) Quality of the surface water of a basin affected by the expansion of the agricultural frontier over the native forest in the Argentine Espinal region. Environ Sci Pollut Res 29:57395–57411. https://doi.org/10.1007/s11356-022-19760-4

Vejre H, Jensen FS, Thorsen BJ (2010) Demonstrating the importance of intangible ecosystem services from peri-urban landscapes. Ecol Complex 7(3):338–348. https://doi.org/10.1016/j.ecocom.2009.09.005

Villegas-Palacio C, Berrouet L, López C et al (2016) Lessons from the integrated valuation of ecosystem services in a developing country: three case studies on ecological, socio-cultural and economic valuation. Ecosyst Serv 22(Part B):297–308. https://doi.org/10.1016/j.ecoser.2016.10.017

Wang J, Koopman KR, Collas FPL et al (2021) Towards an ecosystem service-based method to quantify the filtration services of mussels under chemical exposure. Sci Total Environ 763(2021):144196.  https://doi.org/10.1016/j.scitotenv.2020.144196

Zandebasiri M, Pourhashemi M (2018) Traditional forest-related knowledge, part one: describing the foundations and features of traditional and scientific systems. Iran J Nature 3(2):10–15. https://doi.org/10.22092/IRN.2018.116430

Zandebasiri M, Soosani J, Pourhashemi M (2017) Evaluating existing strategies in environmental crisis of Zagros forests of Iran. Appl Ecol Environ Res 15(3):621–632. https://doi.org/10.15666/aeer/1503_621632

Zandebasiri M, Filipe JA, Soosani J et al (2020) An incomplete information static game evaluating community-based forest management in Zagros Iran. Sustainability 12(1750):1–14. https://doi.org/10.3390/su12051750

Zandebasiri M, Groselj P, Azadi H et al (2021) DPSIR framework priorities and its application to forest management: a fuzzy modeling. Environ Monit Assess 193:598. https://doi.org/10.1007/s10661-021-09257-x

Zandebasiri M, Azadi H, Viira AH et al (2023) Modeling ecosystem functions’ failure modes: formulating fuzzy risk priorities in the forests of Western Iran. Int J Environ Sci Technol 20:2581–2600. https://doi.org/10.1007/s13762-022-04619-5

Zhai Y, Jiang Y, Cao X et al (2022) Valuation of ecosystem damage induced by soil-groundwater pollution in an arid climate area: framework, method and case study. Environ Res 211:113013. https://doi.org/10.1016/j.envres.2022.113013

Download references

Acknowledgements

We are grateful from two anonymous reviewers whose comments were very helpful for this article.

This study was an extension of the resource review phase of a research project in valuing ecosystem services approved by AREEO, Iran with approved code: 4-42-09-125-00127. The Agricultural and Natural Resources Research Center of Chaharmahal and Bakhtiari Province and General Department of Environment of Chaharmahal and Bakhtiari Province, Iran sponsored this project.

Author information

Authors and affiliations.

Research Division of Natural Resources, Chaharmahal and Bakhtiari Agriculture and Natural Resources Research and Education Center, AREEO, Shahrekord, Iran

Mehdi Zandebasiri, Hassan Jahanbazi Goujani & Yaghoub Iranmanesh

Department of Economics and Rural Development, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium

Hossein Azadi

Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 1, 51006, Tartu, Estonia

Ants-Hannes Viira

General Department of Environment, Chaharmahal and Bakhtiari Province, Shahrekord, Iran

Mohsen Habibi

You can also search for this author in PubMed   Google Scholar

Contributions

MZ prepared the original draft. HJG, YI, and MH helped in literature review. HA and AHV enriched and edited the paper in all sections.

Corresponding author

Correspondence to Mehdi Zandebasiri .

Ethics declarations

Ethics approval.

This is not applicable.

Consent for publication

Conflict of interest.

The authors declare no competing interests.

Additional information

Responsible Editor: Philippe Garrigues

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is a review article based on a review of resources related to the valuation of ecosystem services.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Zandebasiri, M., Jahanbazi Goujani, H., Iranmanesh, Y. et al. Ecosystem services valuation: a review of concepts, systems, new issues, and considerations about pollution in ecosystem services. Environ Sci Pollut Res 30 , 83051–83070 (2023). https://doi.org/10.1007/s11356-023-28143-2

Download citation

Received : 01 October 2022

Accepted : 02 June 2023

Published : 20 June 2023

Issue Date : July 2023

DOI : https://doi.org/10.1007/s11356-023-28143-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Classical valuation methods
• Basic value transfer method
• Deliberative ecosystem service valuation
• Climate change
• Find a journal
• Publish with us
• Track your research

The Federal Register

The daily journal of the united states government, request access.

Due to aggressive automated scraping of FederalRegister.gov and eCFR.gov, programmatic access to these sites is limited to access to our extensive developer APIs.

If you are human user receiving this message, we can add your IP address to a set of IPs that can access FederalRegister.gov & eCFR.gov; complete the CAPTCHA (bot test) below and click "Request Access". This process will be necessary for each IP address you wish to access the site from, requests are valid for approximately one quarter (three months) after which the process may need to be repeated.

An official website of the United States government.

If you want to request a wider IP range, first request access for your current IP, and then use the "Site Feedback" button found in the lower left-hand side to make the request.