Assessing Coastal Marshes Ecosystem Services: A Systematic Review of Ecological Indicators

Assessing Coastal Marshes Ecosystem Services: A Systematic Review of Ecological Indicators | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessing Coastal Marshes Ecosystem Services: A Systematic Review of Ecological Indicators Marianna Lanari, Gry Overvad Frederiksberg, Anu Vehmaa, Christoffer Boström, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8864533/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Coastal marshes are heterogeneous habitats that provide multiple ecosystem services (ESs) but have suffered major declines on the global scale. Therefore, the conservation and restoration of marshes are pivotal for biodiversity maintenance and climate change mitigation and adaptation. However, the evaluation of their effectiveness to tackle environmental challenges depends on ESs assessments grounded in ecological indicators, for which comprehensive, updated overviews are lacking. We systematically reviewed the ecological literature to identify the temporal evolution of coastal marsh ESs assessments, along with the diversity and operationalization of ecological indicators. We found that studies on coastal marsh ESs have grown since 2009, with a predominance of research on Climate Regulation, Bioremediation/Water Purification, and Coastal protection-related services. Most studies focused on a single service, overlooking potential synergies and trade-offs among ESs. Furthermore, few ecological studies evaluated social or economic benefits, indicating challenges in effectively communicating human reliance on coastal marshes. The number and type of ecological indicators varied across services. A high diversity of indicators reflected both the maturity of certain ESs and a lack of standardized metrics, indicating that methodological consistency and ecological comprehensiveness remain a challenge. We highlight that multivariate approaches, assessing multiple ESs by using bundles of complementary indicators, will enable more informative assessments. This study provides guidance for selecting appropriate ecological indicators and underscores the need to integrate ecological, social, and economic dimensions of coastal marsh ESs to better support management and policy strategies. Cascade model multifunctionality ecosystem attributes multivariate approach CICES proxies Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 INTRODUCTION Coastal marshes are highly productive wetland habitats located at the interface of terrestrial and marine systems that can be found on every continent except Antarctica (Mcowen et al., 2017 ). They occur in low-energy shores subjected to regular or irregular tidal flooding and are characterized by waterlogged soils and vegetation adapted to salty or brackish conditions (Adam, 1990 ). As their structure and functioning are controlled by several environmental factors that vary globally (e.g., salinity, inundation period, and temperature regime), coastal marshes are very heterogeneous habitats, being also referred to as salt marshes, coastal or seashore meadows, coastal wetlands, or coastal grasslands (Vehmaa et al., 2024 ; Yando et al., 2023 ). Coastal marshes support and provide multiple ecosystem services (hereafter ESs; Barbier et al., 2011 ; Friess et al., 2020 ), many of which are particularly relevant in relation to the current climate and biodiversity crises. Along with seagrasses and mangroves, coastal marshes sustain nursery and feeding grounds for marine mammals, invertebrates, and commercially important fish species (Whitfield, 2017 ). Coastal vegetated areas assimilate and store large amounts of carbon from the atmosphere through the trapping and long-term burial of refractory organic carbon, denominated “blue carbon” (Duarte et al., 2013 ). Sediment stabilization and water storage by herbaceous plants offer coastal protection against storms and flooding events, enhancing the adaptation of coastal livelihoods to extreme weather events (Fairchild et al., 2021 ), while also enhancing water quality through the uptake and storage of nutrients and contaminants (Barbier et al., 2011 ). Coastal marshes additionally provide important cultural services, offering opportunities for recreation, education, and a strong sense of place for local communities (Barbier et al., 2011 ). The protection of threatened coastal marshes and the restoration of lost ones is acknowledged by the IPCC as a contribution to climate change mitigation (IPCC, 2014 ). Such management also underpin climate change adaptation as the marshes help build resilient coastlines to climate-related impacts while simultaneously supporting high faunal and floral diversity (Cadier et al., 2020 ; Girardin et al., 2021 ; Manes et al., 2022 ). Consequently, coastal marsh conservation and restoration efforts have been adopted to re-establish and/or maximize their ESs provision (Liu et al., 2024 ). Robust assessments of the ESs provision of coastal marshes are needed to evaluate their effectiveness in tackling contemporary environmental challenges, to inform decision-making and to guide policy decisions and natural resources management. To do so, indicators have been adopted as measurable variables to quantify the capacity, flow, and value of these services. Such indicators should meet applicability criteria such as measurability, sensitivity, specificity, scalability, and transferability (Atkins et al., 2015 ; Hattam et al., 2015 ) to support monitoring of ecosystem health and analyses of service trade-offs (Cadier et al., 2020 ; Grima et al, 2023 ; Müller et al., 2016 ). Conceptual frameworks such as the “ecosystem services cascade” (hereafter Cascade model; Haines-Young and Potschin, 2010 ; Fig. 1 ) have guided the development of ESs indicators. The Cascade model illustrates the linkages among ecological, social, and economic realms through a cascade of ecosystem properties and functions that generate ESs, which in turn promote benefits to humans that can be valued monetarily or through other means (Potschin and Haines-Young, 2017 ). Thus, the ecological side of the cascade represents the capacity or potential supply of an ESs, whilst the socio-economic side is associated with how these ESs are demanded and valued by society. Because ESs cannot be directly measured (Boerema et al., 2017 ), most studies have assessed biophysical properties and ecological functions as indicators of the capacity of a particular ecosystem to supply a given service (Liquete et al., 2013a ; Raffaelli, 2015 ; Müller et al., 2016 ; Meacham et al., 2022 ). Research on ESs has grown significantly in the last decades (Constanza et al., 2017), and diverse methods have been used to assess indicators, including field measurements, remote sensing, modelling, and qualitative/quantitative surveys (Müller et al., 2016 ). Although no formal guidelines exist for the selection of ES indicators, data compilations have provided information on indicator robustness to support their selection, and to improve the standardization of methods. Most of these compilations have not provided any specific context for the indicators (e.g., a focus on a specific habitat; Boerema et al., 2017 ; Burkhard et al., 2014 ; Feld et al., 2009 ; Maes et al., 2014) or have focused on terrestrial systems (e.g., Egoh et al., 2012). The relatively few compilations for marine and coastal systems have either been quite general and do not refer to specific habitats (e.g., Bӧhnke-Henrichs et al, 2013; Liquete et al., 2013a ) or they have been quite site-specific and thus performed to fit local case study contexts (e.g., Atkins et al., 20415; Hattam et al, 2015 ; Lillebø et al., 2016 ). Even when referring to specific habitats, such as coastal vegetated habitats (e.g., Shepard et al., 2011 ; Bayraktarov et al., 2020 ; Cadier et al., 2020 ), compilations of indicators have mainly addressed “traditional” macro and mesotidal salt marshes and specific services, thus not encompassing the ESs also provided by heterogeneous coastal marsh habitats occurring in microtidal systems and brackish waters. Comprehensive assessments of coastal marsh ES indicators can contribute to the adoption of common methods for ESs assessments under distinct environmental scenarios, which is crucial to analyzing their relevance to tackle contemporary ecological challenges worldwide. By systematically reviewing the literature on coastal marshes, we analyze the indicators of biogeophysical properties and functions being used in ecological studies focused on ESs assessments worldwide. We aim to answer the following questions: (1) What are the main ESs being investigated in coastal marshes worldwide, and how has this research field developed over time? (2) How many indicators are being used to quantify each ESs, and how are these indicators measured in practice? and (3) What type (i.e., ecosystem attributes) of indicators are being applied? By doing so, we provide recommendations for the use of ecological indicators in ESs assessments within coastal marsh habitats. MATERIAL AND METHODS To investigate the ecological indicators used in assessing ESs in coastal marshes, a systematic quantitative literature review was performed using the Scopus and ISI Web of Science databases. Databases were searched through title, abstract and keywords using the following strings: ( "saltmarsh" OR "salt marsh" OR "tidal marsh" OR "brackish marsh" OR "coastal marsh" OR "coastal wetland" OR "coastal meadow" OR "seashore meadow" OR "coastal pasture" OR "reed belt" OR "salt meadow" ) AND ( "ecosystem service" OR "environmental services" OR "ecological services" OR "ecosystem goods and services" OR "benefits to humankind" OR "benefits to human well-being" ). The first part of the search string encompasses the diversity of coastal marshes that occur under distinct environmental conditions worldwide. It includes not only terms describing traditional tidal coastal marshes (e.g., salt marsh, tidal marsh) but also commonly used terms referring to habitats with varying salinity levels and tidal influence (e.g., coastal wetland, coastal meadow, reed belt), following Vehmaa et al. ( 2024 ). Reviews, meta-analyses, perspective and methodological articles, book articles, and grey literature were excluded from our review. Only peer-reviewed, English-written research articles were selected for screening. Literature available until April 2023 (i.e., screening cutoff date) was included. A total of 887 records from Web of Science and 790 records from SCOPUS were found, resulting in 1107 studies for analyses after removal of duplicates (Fig. 2 ). A two-step screening procedure was performed to select the papers to be included. In the first step, studies were screened by reading their abstract to verify whether they contained assessments of coastal marsh ESs. Papers focused on inland wetlands, seagrass and mangroves, or terrestrial habitats were excluded, as well as papers using the term ecosystem service without quantitatively or qualitatively evaluating ESs. The screening was performed independently by two researchers, and internal cross-checking was performed to minimize bias. Whenever the content of the paper abstract was unclear or if questions persisted, the papers were selected for further analysis. At this step, a total of 326 papers were retained for quantitative and qualitative analyses. In the second step, only ecological studies were selected for assessment of the ESs and extraction of the associated indicators. Economic and social science studies purely focused on monetary valuation or qualitative analysis of public perception of coastal marshes ESs without ecological assessments were discarded (i.e., 138 studies) as our review targets the multiple ecological components of the Cascade model. For instance, social science studies such as Thomas et al. ( 2022 ) were based on as interviews, photo elicitations and participatory mapping and word-association techniques. In addition, economic and social science studies often rely on literature-based ESs quantifications derived from ecological indicators that were already captured in our analyses. For instance, Bertram et al. ( 2021 ) estimated the social costs of carbon in blue carbon ecosystems using average annual carbon sequestration rates obtained from global estimates by Ouyang and Lee ( 2014 ). Likewise, Camacho-Valdez et al. ( 2014 ) analyzed the effects of land use changes on ES values in coastal marshes by applying a value transfer method based on land cover data (i.e., habitat area). Importantly, excluding social science studies did not compromise the inclusion of studies assessing Cultural services, as many of these were grounded in quantifiable biophysical properties and functions (e.g., habitat area, number of protected species). Furthermore, three studies were not available for download and were not analyzed. A total of 185 ecological studies were selected for further analysis (Fig. 2 ; Online Resource 1, Table S1 ). ESs were classified for these studies following the Common International Classification of Ecosystem Services (CICES, v5.1; Potschin and Haines-Young, 2016). The CICES classification has a nested hierarchical structure that allows flexible use at different spatial scales and areas of interest. Importantly, the CICES classification resonates with other widely used classifications such as the Millennium Ecosystem Assessment and The Economics of Ecosystems and Biodiversity (TEEB; Potschin and Haines-Young, 2016). At the highest level, three main categories are defined (Provisioning, Regulation and Maintenance, and Cultural), followed by a series of Divisions, Groups, and Classes. In our study, Classes were used to represent the distinct ESs, which, in some cases, were clustered into one as they shared common indicators and were thus difficult to differentiate (Czúcz et al., 2018 ). That is the case for those classes associated with “Bioremediation and water purification”, “Soil quality”, “Recreation and Ecotourism”, “Religious and spiritual value”, and “Scientific, educational, heritage and cultural values” services, among others (Table 1 ). For studies not using the CICES classification, ecosystem services were translated into the CICES framework. Table 1 List of classes from the CICES that were pooled into a single service and their respective category CICES classes (v5.1) Service Category 2.1.1.1- Bioremediation by micro-organisms, algae, plants, and animals 2.1.1.2 - Filtration/sequestration/storage/accumulation by micro-organisms, algae, plants, and animals 2.2.5.2 - Regulation of the chemical condition of salt waters by living processes Bioremediation and water purification Regulating and Maintenance 2.2.1.1 - Control of erosion rates 2.2.1.2 - Buffering and attenuation of mass movement Erosion control 2.2.4.1 - Weathering processes and their effect on soil quality 2.2.4.2 - Decomposition and fixing processes and their effect on soil quality Soil quality 2.1.2.1 - Smell increase 2.1.2.3 - Visual screening Mediation of smell/visual impact 2.2.3.1 - Pest control (including invasive species) 2.2.3.2 - Disease control Pest and disease control 3.2.1.1 - Elements of living systems that have symbolic meaning 3.2.1.2 - Elements of living systems that have sacred or religious meaning 3.2.1.3 - Elements of living systems used for entertainment or representation 3.2.2.1 - Characteristics or features of living systems that have an existence value 3.2.2.2 - Characteristics or features of living systems that have an option or bequest value Religious and spiritual value Cultural 3.1.1.1 - Experiential use of plants, animals and land-/seascapes in different environmental settings. 3.1.1.2 - Physical use of land-/seascapes in different environmental settings Recreation and Tourism 3.1.2.1 - Characteristics of living systems that enable scientific investigation or the creation of traditional ecological knowledge. 3.1.2.2 - Characteristics of living systems that enable education and training. 3.1.2.3 - Characteristics of living systems that are resonant in terms of culture or heritage. 3.1.2.4 - Characteristics of living systems that enable aesthetic experiences Scientific, educational, heritage and cultural values The number of ESs addressed in each study was determined and the indicators used to assess ESs were extracted. Indicators included both ecosystem properties (i.e., biophysical structure of the system, such as biomass, biodiversity indexes, area) and functions (i.e., processes/fluxes that occur in an ecosystem, such as denitrification or carbon sequestration) present in the ecological realm of the ESs Cascade model (sensu Boerema et al, 2017 ). We thus regarded the terms functions and processes as the same according to Wallace ( 2007 ) and Jax ( 2010 ). Following Egoh et al. (2012), we distinguished between parameters and indicators in ESs assessments. Parameters correspond to direct biogeophysical measurements of environmental properties obtained through in situ and remote field sampling, laboratory analyses or ecological modelling (e.g., habitat area, soil dry bulk density and plant nutrient content). Indicators, in contrast, are interpreted or combined variables derived from one or more parameters to directly or indirectly represent ES supply (e.g., carbon stock, wave exposure). Here, indicators can refer to different spatial units because we did not differentiate between local- and regional-scale assessments. We named co-indicators those measurements occurring both as parameters and indicators. The nomenclature of matching parameters and indicators was standardized, and, in some cases, similar indicators were pooled into one for simplification and to enhance data visualization (Online Resource 1,Table S2). The ecological indicators used for the ESs in each category were synthesized quantitatively using Sankey diagrams using the SankeyMATIC website ( www.sankeymatic.com ). Additional bibliometric data on the number of studies per year, the number of studies investigating each ecosystem service, as well as the temporal trends in the ESs investigated, were extracted from the systematic review. Information on the number of ESs investigated, as well as assessments of monetary or social valuation, besides ecological aspects (i.e., a mixed ESs perspective), was also obtained from the selected studies. RESULTS General trends in ESs assessments Assessments of ESs in coastal marshes were found in the literature already from 2009 with an increasing number of studies towards 2023 (Fig. 3 a). Regulating services dominated these assessments whilst cultural services were least investigated (Fig. 3 b). Climate regulation was the most studied ES (i.e., 89 studies), followed by Bioremediation and water purification (60), services associated with Coastal protection (i.e., Flood Protection, Storm Protection and Erosion Control; a total of 50 studies) and Habitat maintenance (20; Fig. 3 b). Bioremediation and water purification dominated the services analyzed in the first decade of the 2000´s with a significant increase in the Climate regulation assessments from 2014 (Fig. 4 a). Overall, temporal increases were observed in the number of studies assessing Climate regulation, Habitat maintenance, and Bioremediation and water purification, with less pronounced increases also evident for coastal protection–related services. For the remaining regulating services, no clear temporal trends were observed (Fig. 4 b). For provisioning services, food provision was the most assessed one with a slight increase in the number of studies from 2014 to 2021 (Fig. 4 c). No temporal trends were observed for cultural services, with Recreation and Tourism, and Aesthetic values being the services most assessed (Fig. 4 d). The majority of studies (~ 75%) analyzed only one ES (Fig. 5 ). From the 185 studies selected for indicators extraction, only 23 adopted a mixed ESs perspective, also assessing components of the socio-economic system according to the Cascade model. Of these, 17 studies included monetary valuation of the assessed ESs, while the remaining six studies evaluated benefits in other ways (e.g., number of houses protected from floods or stakeholders’ perceptions). Ecological indicators for ESs assessments The number of indicators varied among the ESs assessed (Fig. 6 ). The highest number of indicators was found for Bioremediation and water purification whilst the lowest number occurred for Energy source. In general, Regulating services presented the highest numbers of indicators, parameters and co-indicators. A high diversity of biogeophysical parameters and indicators was also identified throughout the distinct categories and services. In some cases, similar measurements were used across distinct ESs, although their role as parameters or indicators varied among services. For instance, soil accretion was applied as a direct indicator for Erosion control but served as a physical parameter in Bioremediation and ater purification and Climate regulation, where it was used to calculate sequestration rates (Fig. 7 ). Similarly, soil dry bulk density was a parameter for Bioremediation and water purification and Climate regulation, while functioning as a direct indicator for Hydrological cycle (Figs. 7 and 8 ). Some indicators also appeared as co-indicators, particularly Habitat area, which was used in almost all ESs analyzed. Habitat area was used solely to represent ES supply, but it was also an important measurement for upscaling other parameters typically measured at smaller spatial scales (e.g., denitrification rates, soil and plant carbon and nutrient content, soil elevation) and for ecological modelling (e.g., Exposure index, Carbon and Habitat quality models). ES values resulting from the combination of Habitat area with ES scores (i.e., numerical or categorical ratings of ESs; see Table S2) were also applied in the assessment of all services. Bioremediation and water purification, was assessed using a total of 23 indicators, including 4 co-indicators. From these, 9 indicators were calculated based on 19 biogeophysical parameters (Figs. 6 and 7 a). Denitrification rates, nutrient stocks and sequestration rates were the most common ES indicators. Habitat maintenance had 17 indicators supported by 8 biogeophysical parameters (Figs. 6 and 7 b). Species diversity and habitat-related indices, such as Habitat quality models and ESs values (i.e., a combination of Habitat area with ES scores), prevailed among the indicators. Coastal protection-related services such as Erosion control, Flood protection and Storm protection had 8, 9 and 9 indicators, respectively (Figs. 6 and 7 c). Wave attenuation, Soil accretion, Surge attenuation and Exposure index, along with Habitat area, prevailed in these studies. A high number of biogeophysical measurements were observed (3, 15 and 10, respectively) for these coastal protection-related ESs. A similar trend was found for Climate Regulation (i.e., 24 measurements; Figs. 6 and 7 d). Carbon stock was the most used indicator for Climate regulation, followed by carbon sequestration and greenhouse gas (GHG) fluxes. The remaining 8 regulating ESs presented a total of 17 indicators (including Habitat area, a co-indicator) with 14 biogeophysical parameters used to calculate them (Figs. 7 a and 8 a). Habitat area was the prevailing indicator in Hydrological cycle, Soil quality, Ventilation and respiration and Microregional climate regulation. A similar trend was observed for provisioning services (Figs. 6 and 8 a). The 5 provisioning services analyzed were investigated by using 13 indicators supported by 4 biogeophysical measurements plus an ES score (Figs., 6 and 8b). Habitat area prevailed as an indicator and was also the only co-indicator. For cultural services, 7 indicators were found of which 2 of them derived from 2 parameters (Figs. 6 and 8 c). Habitat area was the most used indicator and co-indicator for all services, except Religious and Spiritual values (Fig. 8 c). DISCUSSION Our study underscores the increasing recognition of the importance of coastal marshes for human well-being, a trend that likely reflects their growing relevance in addressing current environmental challenges. Despite this progress, there remains a clear need for more comprehensive, interdisciplinary research capable of translating the multiple ESs into effective management actions. By systematically reviewing the literature, our work broadens the range of parameters and indicators reported in previous reviews and highlights that employing bundles of indicators that integrate multiple ecosystem attributes is essential to adequately capture the complexity of coastal marsh ESs. Therefore, our findings offer a comprehensive toolbox and a valuable baseline for future assessments of ES supply in coastal marsh ecosystems. Overview of coastal marshes ESs assessments The marked increase in ESs assessments of coastal marshes since 2009, as observed here, aligns with the rise in general ESs-related publications across terrestrial and aquatic habitats since then (Boerema et al., 2017 ), a trend also noted in assessments of coastal and marine ESs more broadly (Liquete et al., 2013a ). The number of studies investigating ecosystem services in coastal wetlands, such as mangroves and seagrasses, has also increased since 2010, mostly reflecting their relevance for climate mitigation and coastal protection (Bimrah et al., 2022 ; Lima et al., 2023 ). Our findings confirm that, although coastal and marine ESs have historically received less attention than their terrestrial counterparts (Liquete et al., 2013a ; De La Cruz, 2021 ), there has been growing recognition over the past decades of the vital role that coastal wetlands play in supporting human well-being. Regulating services have received more attention than other ESs in marine and coastal literature (e.g., Liquete et al., 2013a ), including seagrass and mangrove studies (Bimrah et al., 2022 ; Lima et al., 2023 ), and our findings reinforce this trend for coastal marshes. The low number of studies assessing Cultural services, on the other hand, corroborates previous findings that such ESs remain difficult to quantify and are understudied in marine and coastal areas (Liquete et al., 2013a ; La Cruz, 2021 ). We observed a shift in the most frequently assessed ESs over the study period, mirroring broader temporal trends reported for coastal wetlands (e.g., Cadier et al., 2020 ). During the 2000s, assessments focused largely on Bioremediation and water purification provided by coastal marshes, likely driven by efforts to mitigate eutrophication, which had become a widely recognized environmental concern by the 1980s and 1990s (Howarth and Marino, 2006 ). In the 2010s, the emergence of climate change concerns and the Blue Carbon agenda, marked by seminal publications such as McLeod et al. ( 2011 ) and Duarte et al. ( 2013 ), contributed to a surge in Climate regulation studies from 2014 onward (Costa and Macreadie, 2022 ). Simultaneously, growing awareness of the value of coastal marshes in coastal hazard mitigation has fuelled assessments of coastal protection-related services (Erosion control, Flood regulation, and Storm protection services). A similar temporal pattern has been reported for coastal wetland restoration projects (e.g., Cadier et al., 2022), indicating that assessments of ESs in coastal marshes not only reflect evolving scientific and societal priorities but also align with shifts in research funding agendas over recent decades. The unique location of coastal marshes at the land-sea interface makes them a multifunctional system that simultaneously provides multiple ecosystem functions and services (Barbier et al., 2011 ). Despite this, we found that most studies assessed only one or a few services, hence overlooking ESs bundles (i.e, co-occurring sets of ESs) and their potential synergies and trade-offs (Alemu et al., 2024 ; Mason et al., 2025 ; Reader et al., 2024 ). For instance, cattle grazing in coastal marshes may enhance Provisioning and Cultural services while negatively impacting Coastal protection, Habitat maintenance, and Climate mitigation (Davidson et al., 2017 ; Graversen et al., 2022 ; Marin-Díaz et al., 2021; Zhang et al., 2021 ). Additionally, caution is needed to avoid the overrepresentation of certain ESs—particularly those that are easier to quantify in monetary terms—which can skew decision-making and undervalue other, less tangible but equally important services such as Spiritual and religious values, for instance (Boerema et al., 2017 ). Coastal marshes’ multifunctionality also entails economic and social benefits, as highlighted by frameworks such as the Cascade model. However, such frameworks are only useful if the full spectrum of the Cascade is investigated (La Notte et al., 2017 ). Our findings indicate that only a small number of studies extended beyond the ecological realm of the framework, suggesting a disconnect between how coastal marshes function and how they are perceived and valued by society. Coastal marshes are often undervalued habitats, with limited public awareness of their societal benefits (Rendon et al., 2019 ; McKinley et al., 2020). Information on the ESs benefits derived from coastal marshes’ ecological functioning can help bridge knowledge gaps and solve controversies between scientists and citizens. For instance, marsh restoration and conservation actions may re-establish some ESs, such as Storm protection, while limiting access to recreational activities. Clear communication of how ecological functioning underpins long-term benefits can ultimately foster societal support to management initiatives (Gaspers et al., 2024 ; Grindsted et al., 2025 ). In addition, monetary valuation of coastal habitats ESs provides a useful decision-support tool when properly used allowing these habitats to be included in decision-making frameworks and attracting funding for conservation and restoration (zu Ermgassen et al., 2021 ). Therefore, despite the substantial increase in coastal wetland ESs assessments over the past decade, further efforts are needed by ecologists to effectively communicate human reliance on natural ecosystems. While striving to highlight ESs through quantification, we must also acknowledge that Nature’s existence value and intrinsic worth cannot be monetized. As Dasgupta ( 2021 ) puts it in this review of the economics of biodiversity, “One may doubt, however, that hard-nosed cost-benefit analyses could be the right language in which to express all values. [..] but we do not put a price on the sacred. Our urge is simply to protect it.” Number of indicators Biogeophysical measurements of ecosystems is a fundamental step in estimating the provision of ESs and their associated benefits and costs (Grima et al., 2023 ). In our analysis, Regulating services had the highest number of indicators, whereas Cultural services had the fewest. The indicators identified in this study align with those used to measure coastal protection-related services, carbon and nutrient dynamics, and primary and secondary production, reported in previous reviews on coastal wetland and marine systems (e.g., Shepard et al., 2011 ; Liquete et al., 2013a , b ; Cadier et al., 2020 ). Nonetheless, our study expanded the number of parameters and indicators used, as well as the number of ESs evaluated, which may serve as a toolbox and baseline information for future coastal marsh ESs assessments. The high number of parameters and associated indicators observed for certain ESs may reflect methodological advancements, including the use of increasingly complex, process-based indicators and models. Frequently studied ESs, such as Bioremediation and water purification, Habitat maintenance, and Coastal protection-related services, often rely on indexes and ecological modelling, which explains the high number of both parameters and indicators associated with these services. For instance, whilst services such as Erosion Control and Storm protection tend to be assessed through straightforward measurements of soil accretion/elevation and wave attenuation, respectively, Flood protection often relies on the use of more complex measurements and modelling, as also noted by Shepard and collaborators (2011). Additionally, certain Regulating ESs are composed of multiple components, further contributing to indicator diversity (Boerema et al., 2017 ). Indicators of Bioremediation and water purification often encompass various stages of nitrogen cycling (e.g., nitrification, denitrification) across different environmental compartments, including the water column, porewater, and soils. On the other hand, a high diversity of indicators may also reflect a lack of methodological consistency for certain ESs, potentially hindering comparisons across studies (Cadier et al., 2020 ). The low number of indicators identified for services such as Climate regulation and Coastal protection-related studies suggests a high degree of consensus in their assessments. Accordingly, efforts to standardize sampling protocols and analytical approaches within the Blue Carbon research community in the last decade (e.g., Costa and Macreadie, 2022 ; Dahl et al., 2025 ). However, few studies assessed both carbon sequestration and GHG emissions (here named C budget), thereby providing a more comprehensive view of the climate benefits provided by coastal marshes (Dahl et al., 2025 ; Williamson and Gattuso, 2022; Kristensen et al., 2025 ). Indeed, measurements of GHG fluxes in coastal wetlands are still scarce in the literature, especially if compared with Blue Carbon sequestration assessments (Cadier et al., 2020 ). Similar patterns were observed for other services, such as Bioremediation and water purification, and Habitat maintenance, where methodological consistency (i.e., the predominant use of a few indicators) was not always accompanied by comprehensive assessments of service components. Therefore, achieving both methodological consistency and ecological comprehensiveness in the use of indicators remains a key challenge in the assessment of coastal marsh ESs. In this sense, we suggest that using bundles of indicators is necessary to fully capture the complexity and functioning of ESs provided by coastal marshes. Types of indicators The use of appropriate indicators is essential for accurately assessing ESs and several ecosystem attributes such as diversity, structure, and function have been employed for this purpose (Broszeit et al., 2017 ; Egoh et al., 2012; Ruiz-Jaen and Aide, 2005 ). For provisioning services, structural indicators such as habitat area, annual catch, and yield (both annual and areal) were predominant, supporting the relevance of structural attributes in evaluating this service category (La Notte et al., 2017 ). Regulating services, in turn, were more often assessed using functional indicators (e.g., carbon and nutrient fluxes, erosion control, and wave attenuation) derived from biogeochemical parameters and statistical modeling of interactions between biotic and abiotic components. However, we observed that several Regulating services are still commonly assessed using indicators that reflect ecosystem properties (e.g., carbon and nutrient stocks) rather than ecosystem functions (e.g., carbon and nutrient accumulation rates. While stock measurements provide insights into the potential capacity of an ecosystem to supply a service, they do not account for the temporal scale and dynamics in the functions providing ESs (Boerema et al., 2017 ; Cadier et al., 2020 ; Garland et al., 2020). The use of Habitat area as an indicator underscores the growing role of remote sensing in ESs mapping and monitoring, as it provides spatially explicit, consistent, and repeatable data across large areas and timeframes (Grima et al., 2023 , and references therein). However, the widespread use of Habitat area as a single indicator of Provisioning and Cultural services, but also some Regulating ones, can lead to over- or underestimation of actual ESs provision (Schröter et al., 2021 ). In coastal marshes, ESs provision varies with factors such as species composition, tidal dynamics, geomorphology, and soil characteristics (e.g., Duarte et al., 2021 ; Leivas-Dueñas et al., 2024; Spencer and Harvey, 2012 ), which are not captured by areal estimates alone. Nonetheless, if combined with other functional parameters measured at smaller spatial scales (e.g., m 2 ), Habitat area can be an important indicator allowing upscaling ESs provisions to the habitat level. Indeed, we found that for most ESs investigated, spatial modeling often incorporated Habitat area, a structural metric, as a parameter combined with functional attributes to map coastal marshes' ESs provision. Tools like InVEST (Natural Capital Model, 2025) integrate habitat area with biophysical data to model changes in ESs provision driven by land-use change, enabling scenario analyses for conservation and land management (Meraj et al., 2022 ). The reliability of such models depends heavily on parameterization and calibration with local data derived from field measurements or literature to ensure accurate outputs (Meraj et al., 2022 ; Peh et al., 2013 ; Schröter et al., 2021 ), hence highlighting how ESs assessments can benefit from combining different ecosystem attributes (Ruiz-Jaen and Aide, 2005 ). Our findings provide important insights regarding the use of ecological indicators in coastal marsh ESs assessments However, many ecological studies, do not explicitly frame their findings within the ESs framework and/or were performed before the concept was coined, a pattern previously observed in reviews for seagrasses (e.g., Ruiz-Frau et al., 2017 ) and salt marshes (e.g., Shepard et al., 2011 ). In many cases, the term ES is only mentioned in the Discussion section or is not mentioned at all, limiting our ability to identify such studies through conventional database searches using titles, abstracts, and keywords. We hence acknowledge that a substantial body of ecological literature on the functioning of coastal marsh habitats that could be translated into ESs assessments was not present in our analysis; however, including all those studies would make the systematic review unfeasible. Despite these limitations, we are confident that our analysis captures, if not all, most of the ecological indicators currently applied in coastal marsh ESs assessments. Conclusions The present study indicates that although significant progress has been made in assessing coastal marshes´ ESs in the last decades, some challenges persist. Regulating and Provisioning services are better characterized in coastal marshes, whilst Cultural services are still understudied, limiting comprehensive assessments of ESs synergies and trade-offs. The few interdisciplinary assessments, combined with the predominance of single-service evaluations, also indicates that the ESs provided by coastal marshes may be inadequately conveyed to stakeholders and insufficiently integrated into coastal management strategies. Future studies should be conducted by interdisciplinary groups and consider the full range of ESs provided by coastal marshes to better inform coastal management. Assessments of coastal marsh ESs should preferably use bundles of complementary ecological indicators, as single indicators are typically insufficient to capture the complexity of ESs. Importantly, such a multivariate approach must encompass not only several indicators but also distinct ecosystem attributes, including functional ones. Finally, managers would benefit if ecological studies would be explicitly framed into the ESs concept, thereby enhancing the translation of ecological findings into monetary and societal benefits to support informed decision-making. Declarations Competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This research was part of the NordSalt project funded through the 2019–2020 BiodivERsA joint call for research proposals, under the BiodivClim ERA-Net COFUND programme, and with the funding organisations: Innovation Fund Denmark (ID), The Academy of Finland (AKA), German Research Foundation (DFG), The Research Council of Norway (RCN), and The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS). Authors’ contributions: ML : Conceptualization, Data curation, Investigation, Methodology, Formal analysis, Visualization, Writing – original draft, Writing – review & editing. GOF : Conceptualization, Data curation, Investigation, Methodology, Validation, Writing – review & editing. AV : Methodology, Writing – review & editing. CB : Writing – review & editing. DKJ : Writing – review & editing. KJ : Writing – review & editing. COQ : Conceptualization, Writing – review & editing. GB : Conceptualization, Funding acquisition, Methodology, Validation, Supervision, Writing – review & editing. Acknowledgements We are grateful to Thea Marie Drachen, from the library of the University of Southern Denmark, for assistance with the databases searches. References Adam, P. 1990. Saltmarsh Ecology . Cambridge, UK: Cambridge University Press. Alemu, I., J. B. Ofsthun, C. Medley, G. Bowden, A. Cammett, A. Gildesgame, E. Munoz, S. E. Stubbins, A., and Randall Hughes, A. 2024. 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Estuaries and Coasts , 44 (6), 1691–1698. https://doi.org/10.1007/s12237-021-00952-z Supplementary Files LanarietalSupplementarymaterialfinalversion.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 23 Feb, 2026 Reviewers invited by journal 19 Feb, 2026 Editor assigned by journal 12 Feb, 2026 First submitted to journal 12 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8864533","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":594042215,"identity":"4dbc6b12-4d04-4204-864a-659ba053d893","order_by":0,"name":"Marianna Lanari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAl0lEQVRIiWNgGAWjYDACdhBRwcDYwMBgTKQWZhBxhmQtjG2kaNFtZn724Oe8OtkNB5g3GxClxewwm7lh77bDxhsOsBUnEKmFwUyCd9uBxA0HeIwPEKmF/Zvk3zl1JGnhMZPmbWAGayHWYTxl0jLHDhvPPMxWTKT3j7dvk3xTUyfbd7x5swRRWhCAmUT1o2AUjIJRMArwAAA2my40KAHChQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-0367-8119","institution":"University of Southern Denmark: Syddansk Universitet","correspondingAuthor":true,"prefix":"","firstName":"Marianna","middleName":"","lastName":"Lanari","suffix":""},{"id":594042216,"identity":"7a417bb6-ad1f-4852-af2a-dd1524d8cd18","order_by":1,"name":"Gry Overvad Frederiksberg","email":"","orcid":"","institution":"University of Southern Denmark: Syddansk Universitet","correspondingAuthor":false,"prefix":"","firstName":"Gry","middleName":"Overvad","lastName":"Frederiksberg","suffix":""},{"id":594042217,"identity":"d804747f-f722-4eed-b741-4cf55dbd41e5","order_by":2,"name":"Anu Vehmaa","email":"","orcid":"","institution":"Turku University of Applied Sciences: Turun Ammattikorkeakoulu","correspondingAuthor":false,"prefix":"","firstName":"Anu","middleName":"","lastName":"Vehmaa","suffix":""},{"id":594042218,"identity":"f9b4e070-2e87-4bb4-bc14-e4b072155883","order_by":3,"name":"Christoffer Boström","email":"","orcid":"","institution":"Abo Akademi University: Abo Akademi","correspondingAuthor":false,"prefix":"","firstName":"Christoffer","middleName":"","lastName":"Boström","suffix":""},{"id":594042219,"identity":"9efdbb90-1e20-4222-b845-3e9f99647434","order_by":4,"name":"Dorte Krause-Jensen","email":"","orcid":"","institution":"Aarhus University: Aarhus Universitet","correspondingAuthor":false,"prefix":"","firstName":"Dorte","middleName":"","lastName":"Krause-Jensen","suffix":""},{"id":594042220,"identity":"4801098b-da10-45c5-a2da-ed1e7b5eef67","order_by":5,"name":"Kai Jensen","email":"","orcid":"","institution":"University of Hamburg: Universitat Hamburg","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Jensen","suffix":""},{"id":594042221,"identity":"33b90ef9-d206-4e81-9885-6fc5ea834fba","order_by":6,"name":"Cintia Organo Quintana","email":"","orcid":"","institution":"University of Southern Denmark: Syddansk Universitet","correspondingAuthor":false,"prefix":"","firstName":"Cintia","middleName":"Organo","lastName":"Quintana","suffix":""},{"id":594042222,"identity":"584f6a5d-5ae6-42ad-9e24-d65247c4bb8c","order_by":7,"name":"Gary Banta","email":"","orcid":"","institution":"University of Southern Denmark: Syddansk Universitet","correspondingAuthor":false,"prefix":"","firstName":"Gary","middleName":"","lastName":"Banta","suffix":""}],"badges":[],"createdAt":"2026-02-12 17:12:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8864533/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8864533/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103300406,"identity":"563ed7d1-4cf2-4446-b092-b17e48f15d60","added_by":"auto","created_at":"2026-02-24 08:00:06","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":333742,"visible":true,"origin":"","legend":"\u003cp\u003eThe Cascade model adapted from Potschin \u0026amp; Haines-Young (2011). The right side of the cascade represents the capacity or potential supply of an ES whilst the left side is associated with how these ESs are demanded and valued by society. The location of biogeophysical properties and ecological functions here investigated are highlighted in the Cascade\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8864533/v1/4ac70cbcc562921c88343895.jpeg"},{"id":103300407,"identity":"93f3a0fa-f548-4e9e-95cd-5d8e3eea2c87","added_by":"auto","created_at":"2026-02-24 08:00:06","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":521742,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of the methodology and selection process used in the present review according to the PRISMA 2020\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8864533/v1/526371042c345607dbe9415b.jpeg"},{"id":103300408,"identity":"34e51d9a-f986-4981-9081-70313eb7ab66","added_by":"auto","created_at":"2026-02-24 08:00:06","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":383350,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trend in the number of studies assessing coastal marshes’ ESs (a) and the number of studies per ES (b). ESs were classified following the Common International Classification of Ecosystem Services (CICES, v5.1; Potschin and Haines-Young, 2016). Bioremediation = Bioremediation/Water purification; Microreg. Clim. Reg. = Microregional climate regulation; Hydro. cycle = Hydrological cycle; Habitat maint. = Habitat maintenance; Mediation of impacts = Mediation of noise/smell/visual impacts; Pest/Dis. control = Pest and disease control; Pol./Seed disp. = Pollination and seed dispersal; Vent./Transp. = Ventilation and transpiration; Fibers and others = Fiber and other material; Recreation = Recreation and tourism; Sci. Edu. Her. val. = Scientific, Educational, Heritage and Cultural values; Spiritual value = Spiritual and Religious values\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8864533/v1/aa5a3ed55e6221388064fe12.jpeg"},{"id":103300414,"identity":"ba200e08-6e09-460e-8540-3c3d95187c7b","added_by":"auto","created_at":"2026-02-24 08:00:07","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":403543,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trends in the number of studies assessing (a) Climate Regulation, Habitat Maintenance, Bioremediation and water quality, and coastal protection-related services, (b) Remaining regulating services, (c) Provisioning services, and (d) Cultural Services. The most studied regulating services are depicted separately from the remaining services from the same category to improve visualization\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8864533/v1/801ffed43da48ef419de311a.jpeg"},{"id":103300411,"identity":"5b8688d1-519a-456e-a982-6ec906439c65","added_by":"auto","created_at":"2026-02-24 08:00:06","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":95740,"visible":true,"origin":"","legend":"\u003cp\u003eThe number of ESs being assessed in the included studies\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8864533/v1/9968471c089174d72dd09992.jpeg"},{"id":103505962,"identity":"cb3990fa-8631-431e-a6a0-58635b69a2d4","added_by":"auto","created_at":"2026-02-26 13:33:39","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":366303,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of parameters, indicators and co-indicators for (a) Regulating and (b) Provisioning and Cultural ecosystem services (according to CICES v5.1; Potschin and Haines-Young, 2016). Parameters are direct biophysical measurements, whereas indicators are derived or processed variables that use one or more parameters. Co-indicators are those measurements/variables occurring both as parameters and primary indicators. Microreg. Clim. Reg. = Microregional climate regulation; Hydro. cycle = Hydrological cycle; Mediation of impacts = Mediation of noise/smell/visual impacts; Pol./Seed disp. = Pollination and seed dispersal; Pest/Dis. control = Pest and disease control; Vent. \u0026amp;Transp. = Ventilation and transpiration; Fibers and others = Fiber and other material; Sci. edu. her. val. \u0026amp; cul. = Scientific, Educational, Heritage and Cultural values\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8864533/v1/ebf907792d73b56a7eb63bd2.jpeg"},{"id":103300410,"identity":"d602b247-5404-4148-8730-e6223c7bfd1c","added_by":"auto","created_at":"2026-02-24 08:00:06","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1562832,"visible":true,"origin":"","legend":"\u003cp\u003eFrom left to right: biogeophysical parameters and indicators being used to assess the regulating services (a) Bioremediation and Water purification, (b) Habitat maintenance, (c) Coastal protection-related services (Erosion control, Flood protection and Storm protection) and (d) Climate regulation. Parameters are direct biophysical measurements, whereas indicators are derived or processed variables that use one or more parameters. Lines thickness denotes the number of times a given parameter or indicator is being used. Asterisks highlight co-indicators, which reflect measurements/variables occurring both as parameters and primary indicators. Bioremediation = Bioremediation/Water purification\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8864533/v1/6a886917f1400d2b0ced3c18.jpeg"},{"id":103300412,"identity":"3e59bd8e-eb16-4265-8eae-9ff4fdacd353","added_by":"auto","created_at":"2026-02-24 08:00:06","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1044923,"visible":true,"origin":"","legend":"\u003cp\u003eFrom left to right: biogeophysical parameters and indicators being used to assess (a) Remaining regulating services, (b) Provisioning services and (c) Cultural services. Parameters are direct biophysical measurements, whereas indicators are derived or processed variables that use one or more parameters. Lines thickness denotes the number of times a given parameter or indicator is being used. Asterisks highlight co-indicators, which reflect measurements/variables occurring both as parameters and primary indicators. Microreg. Clim. Reg. = Microregional climate regulation; Hydro. cycle = Hydrological cycle; Mediation of impacts = Mediation of noise/smell/visual impacts; Pol./Seed disp. = Pollination and seed dispersal; Vent. \u0026amp;Transp. = Ventilation and transpiration; Fibers and others = Fiber and other material; Sci. edu. her. val. \u0026amp; cul. = Scientific, Educational, Heritage and Cultural values\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8864533/v1/e1480807dd4ebd59308de3fd.jpeg"},{"id":104397664,"identity":"39b548b7-fcc8-40de-b963-3ba0cabb409e","added_by":"auto","created_at":"2026-03-11 11:54:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5421639,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8864533/v1/67b0e428-71fd-464c-af45-3633d49a0cfa.pdf"},{"id":103300413,"identity":"9388b9d0-152c-4c77-9c31-0a98877b944e","added_by":"auto","created_at":"2026-02-24 08:00:07","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":106454,"visible":true,"origin":"","legend":"","description":"","filename":"LanarietalSupplementarymaterialfinalversion.docx","url":"https://assets-eu.researchsquare.com/files/rs-8864533/v1/e4a0a142620b6e3781cfe956.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eAssessing Coastal Marshes Ecosystem Services: A Systematic Review of Ecological Indicators\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCoastal marshes are highly productive wetland habitats located at the interface of terrestrial and marine systems that can be found on every continent except Antarctica (Mcowen et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). They occur in low-energy shores subjected to regular or irregular tidal flooding and are characterized by waterlogged soils and vegetation adapted to salty or brackish conditions (Adam, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). As their structure and functioning are controlled by several environmental factors that vary globally (e.g., salinity, inundation period, and temperature regime), coastal marshes are very heterogeneous habitats, being also referred to as salt marshes, coastal or seashore meadows, coastal wetlands, or coastal grasslands (Vehmaa et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Yando et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCoastal marshes support and provide multiple ecosystem services (hereafter ESs; Barbier et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Friess et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), many of which are particularly relevant in relation to the current climate and biodiversity crises. Along with seagrasses and mangroves, coastal marshes sustain nursery and feeding grounds for marine mammals, invertebrates, and commercially important fish species (Whitfield, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Coastal vegetated areas assimilate and store large amounts of carbon from the atmosphere through the trapping and long-term burial of refractory organic carbon, denominated \u0026ldquo;blue carbon\u0026rdquo; (Duarte et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Sediment stabilization and water storage by herbaceous plants offer coastal protection against storms and flooding events, enhancing the adaptation of coastal livelihoods to extreme weather events (Fairchild et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), while also enhancing water quality through the uptake and storage of nutrients and contaminants (Barbier et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Coastal marshes additionally provide important cultural services, offering opportunities for recreation, education, and a strong sense of place for local communities (Barbier et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The protection of threatened coastal marshes and the restoration of lost ones is acknowledged by the IPCC as a contribution to climate change mitigation (IPCC, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Such management also underpin climate change adaptation as the marshes help build resilient coastlines to climate-related impacts while simultaneously supporting high faunal and floral diversity (Cadier et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Girardin et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Manes et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Consequently, coastal marsh conservation and restoration efforts have been adopted to re-establish and/or maximize their ESs provision (Liu et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRobust assessments of the ESs provision of coastal marshes are needed to evaluate their effectiveness in tackling contemporary environmental challenges, to inform decision-making and to guide policy decisions and natural resources management. To do so, indicators have been adopted as measurable variables to quantify the capacity, flow, and value of these services. Such indicators should meet applicability criteria such as measurability, sensitivity, specificity, scalability, and transferability (Atkins et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Hattam et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) to support monitoring of ecosystem health and analyses of service trade-offs (Cadier et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Grima et al, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; M\u0026uuml;ller et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Conceptual frameworks such as the \u0026ldquo;ecosystem services cascade\u0026rdquo; (hereafter Cascade model; Haines-Young and Potschin, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) have guided the development of ESs indicators. The Cascade model illustrates the linkages among ecological, social, and economic realms through a cascade of ecosystem properties and functions that generate ESs, which in turn promote benefits to humans that can be valued monetarily or through other means (Potschin and Haines-Young, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Thus, the ecological side of the cascade represents the capacity or potential supply of an ESs, whilst the socio-economic side is associated with how these ESs are demanded and valued by society. Because ESs cannot be directly measured (Boerema et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), most studies have assessed biophysical properties and ecological functions as indicators of the capacity of a particular ecosystem to supply a given service (Liquete et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e; Raffaelli, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; M\u0026uuml;ller et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Meacham et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResearch on ESs has grown significantly in the last decades (Constanza et al., 2017), and diverse methods have been used to assess indicators, including field measurements, remote sensing, modelling, and qualitative/quantitative surveys (M\u0026uuml;ller et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Although no formal guidelines exist for the selection of ES indicators, data compilations have provided information on indicator robustness to support their selection, and to improve the standardization of methods. Most of these compilations have not provided any specific context for the indicators (e.g., a focus on a specific habitat; Boerema et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Burkhard et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Feld et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Maes et al., 2014) or have focused on terrestrial systems (e.g., Egoh et al., 2012). The relatively few compilations for marine and coastal systems have either been quite general and do not refer to specific habitats (e.g., Bӧhnke-Henrichs et al, 2013; Liquete et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e) or they have been quite site-specific and thus performed to fit local case study contexts (e.g., Atkins et al., 20415; Hattam et al, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lilleb\u0026oslash; et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Even when referring to specific habitats, such as coastal vegetated habitats (e.g., Shepard et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Bayraktarov et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Cadier et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), compilations of indicators have mainly addressed \u0026ldquo;traditional\u0026rdquo; macro and mesotidal salt marshes and specific services, thus not encompassing the ESs also provided by heterogeneous coastal marsh habitats occurring in microtidal systems and brackish waters. Comprehensive assessments of coastal marsh ES indicators can contribute to the adoption of common methods for ESs assessments under distinct environmental scenarios, which is crucial to analyzing their relevance to tackle contemporary ecological challenges worldwide.\u003c/p\u003e \u003cp\u003eBy systematically reviewing the literature on coastal marshes, we analyze the indicators of biogeophysical properties and functions being used in ecological studies focused on ESs assessments worldwide. We aim to answer the following questions: (1) What are the main ESs being investigated in coastal marshes worldwide, and how has this research field developed over time? (2) How many indicators are being used to quantify each ESs, and how are these indicators measured in practice? and (3) What type (i.e., ecosystem attributes) of indicators are being applied? By doing so, we provide recommendations for the use of ecological indicators in ESs assessments within coastal marsh habitats.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cp\u003eTo investigate the ecological indicators used in assessing ESs in coastal marshes, a systematic quantitative literature review was performed using the Scopus and ISI Web of Science databases. Databases were searched through title, abstract and keywords using the following strings: (\u003cem\u003e\"saltmarsh\" OR \"salt marsh\" OR \"tidal marsh\" OR \"brackish marsh\" OR \"coastal marsh\" OR \"coastal wetland\" OR \"coastal meadow\" OR \"seashore meadow\" OR \"coastal pasture\" OR \"reed belt\" OR \"salt meadow\"\u003c/em\u003e) AND (\u003cem\u003e\"ecosystem service\" OR \"environmental services\" OR \"ecological services\" OR \"ecosystem goods and services\" OR \"benefits to humankind\" OR \"benefits to human well-being\"\u003c/em\u003e). The first part of the search string encompasses the diversity of coastal marshes that occur under distinct environmental conditions worldwide. It includes not only terms describing traditional tidal coastal marshes (e.g., salt marsh, tidal marsh) but also commonly used terms referring to habitats with varying salinity levels and tidal influence (e.g., coastal wetland, coastal meadow, reed belt), following Vehmaa et al. (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Reviews, meta-analyses, perspective and methodological articles, book articles, and grey literature were excluded from our review. Only peer-reviewed, English-written research articles were selected for screening. Literature available until April 2023 (i.e., screening cutoff date) was included. A total of 887 records from Web of Science and 790 records from SCOPUS were found, resulting in 1107 studies for analyses after removal of duplicates (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA two-step screening procedure was performed to select the papers to be included. In the first step, studies were screened by reading their abstract to verify whether they contained assessments of coastal marsh ESs. Papers focused on inland wetlands, seagrass and mangroves, or terrestrial habitats were excluded, as well as papers using the term ecosystem service without quantitatively or qualitatively evaluating ESs. The screening was performed independently by two researchers, and internal cross-checking was performed to minimize bias. Whenever the content of the paper abstract was unclear or if questions persisted, the papers were selected for further analysis. At this step, a total of 326 papers were retained for quantitative and qualitative analyses.\u003c/p\u003e \u003cp\u003eIn the second step, only ecological studies were selected for assessment of the ESs and extraction of the associated indicators. Economic and social science studies purely focused on monetary valuation or qualitative analysis of public perception of coastal marshes ESs without ecological assessments were discarded (i.e., 138 studies) as our review targets the multiple ecological components of the Cascade model. For instance, social science studies such as Thomas et al. (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) were based on as interviews, photo elicitations and participatory mapping and word-association techniques. In addition, economic and social science studies often rely on literature-based ESs quantifications derived from ecological indicators that were already captured in our analyses. For instance, Bertram et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) estimated the social costs of carbon in blue carbon ecosystems using average annual carbon sequestration rates obtained from global estimates by Ouyang and Lee (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Likewise, Camacho-Valdez et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) analyzed the effects of land use changes on ES values in coastal marshes by applying a value transfer method based on land cover data (i.e., habitat area). Importantly, excluding social science studies did not compromise the inclusion of studies assessing Cultural services, as many of these were grounded in quantifiable biophysical properties and functions (e.g., habitat area, number of protected species). Furthermore, three studies were not available for download and were not analyzed. A total of 185 ecological studies were selected for further analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e; Online Resource 1, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eESs were classified for these studies following the Common International Classification of Ecosystem Services (CICES, v5.1; Potschin and Haines-Young, 2016). The CICES classification has a nested hierarchical structure that allows flexible use at different spatial scales and areas of interest. Importantly, the CICES classification resonates with other widely used classifications such as the Millennium Ecosystem Assessment and The Economics of Ecosystems and Biodiversity (TEEB; Potschin and Haines-Young, 2016). At the highest level, three main categories are defined (Provisioning, Regulation and Maintenance, and Cultural), followed by a series of Divisions, Groups, and Classes. In our study, Classes were used to represent the distinct ESs, which, in some cases, were clustered into one as they shared common indicators and were thus difficult to differentiate (Cz\u0026uacute;cz et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). That is the case for those classes associated with \u0026ldquo;Bioremediation and water purification\u0026rdquo;, \u0026ldquo;Soil quality\u0026rdquo;, \u0026ldquo;Recreation and Ecotourism\u0026rdquo;, \u0026ldquo;Religious and spiritual value\u0026rdquo;, and \u0026ldquo;Scientific, educational, heritage and cultural values\u0026rdquo; services, among others (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For studies not using the CICES classification, ecosystem services were translated into the CICES framework.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of classes from the CICES that were pooled into a single service and their respective category\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCICES classes (v5.1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eService\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.1.1.1- Bioremediation by micro-organisms, algae, plants, and animals\u003c/p\u003e \u003cp\u003e2.1.1.2 - Filtration/sequestration/storage/accumulation by micro-organisms, algae, plants, and animals\u003c/p\u003e \u003cp\u003e2.2.5.2 - Regulation of the chemical condition of salt waters by living processes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBioremediation and water purification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eRegulating and Maintenance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.2.1.1 - Control of erosion rates\u003c/p\u003e \u003cp\u003e2.2.1.2 - Buffering and attenuation of mass movement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eErosion control\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.2.4.1 - Weathering processes and their effect on soil quality\u003c/p\u003e \u003cp\u003e2.2.4.2 - Decomposition and fixing processes and their effect on soil quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSoil quality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.1.2.1 - Smell increase\u003c/p\u003e \u003cp\u003e2.1.2.3 - Visual screening\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMediation of smell/visual impact\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.2.3.1 - Pest control (including invasive species)\u003c/p\u003e \u003cp\u003e2.2.3.2 - Disease control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePest and disease control\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.2.1.1 - Elements of living systems that have symbolic meaning\u003c/p\u003e \u003cp\u003e3.2.1.2 - Elements of living systems that have sacred or religious meaning\u003c/p\u003e \u003cp\u003e3.2.1.3 - Elements of living systems used for entertainment or representation\u003c/p\u003e \u003cp\u003e3.2.2.1 - Characteristics or features of living systems that have an existence value\u003c/p\u003e \u003cp\u003e3.2.2.2 - Characteristics or features of living systems that have an option or bequest value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReligious and spiritual value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCultural\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.1.1.1 - Experiential use of plants, animals and land-/seascapes in different environmental settings.\u003c/p\u003e \u003cp\u003e3.1.1.2 - Physical use of land-/seascapes in different environmental settings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRecreation and Tourism\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.1.2.1 - Characteristics of living systems that enable scientific investigation or the creation of traditional ecological knowledge.\u003c/p\u003e \u003cp\u003e3.1.2.2 - Characteristics of living systems that enable education and training.\u003c/p\u003e \u003cp\u003e3.1.2.3 - Characteristics of living systems that are resonant in terms of culture or heritage.\u003c/p\u003e \u003cp\u003e3.1.2.4 - Characteristics of living systems that enable aesthetic experiences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScientific, educational, heritage and cultural values\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe number of ESs addressed in each study was determined and the indicators used to assess ESs were extracted. Indicators included both ecosystem properties (i.e., biophysical structure of the system, such as biomass, biodiversity indexes, area) and functions (i.e., processes/fluxes that occur in an ecosystem, such as denitrification or carbon sequestration) present in the ecological realm of the ESs Cascade model (sensu Boerema et al, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). We thus regarded the terms functions and processes as the same according to Wallace (\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and Jax (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Following Egoh et al. (2012), we distinguished between parameters and indicators in ESs assessments. Parameters correspond to direct biogeophysical measurements of environmental properties obtained through in situ and remote field sampling, laboratory analyses or ecological modelling (e.g., habitat area, soil dry bulk density and plant nutrient content). Indicators, in contrast, are interpreted or combined variables derived from one or more parameters to directly or indirectly represent ES supply (e.g., carbon stock, wave exposure). Here, indicators can refer to different spatial units because we did not differentiate between local- and regional-scale assessments. We named co-indicators those measurements occurring both as parameters and indicators. The nomenclature of matching parameters and indicators was standardized, and, in some cases, similar indicators were pooled into one for simplification and to enhance data visualization (Online Resource 1,Table S2). The ecological indicators used for the ESs in each category were synthesized quantitatively using Sankey diagrams using the SankeyMATIC website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.sankeymatic.com\" target=\"_blank\"\u003ewww.sankeymatic.com\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.sankeymatic.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdditional bibliometric data on the number of studies per year, the number of studies investigating each ecosystem service, as well as the temporal trends in the ESs investigated, were extracted from the systematic review. Information on the number of ESs investigated, as well as assessments of monetary or social valuation, besides ecological aspects (i.e., a mixed ESs perspective), was also obtained from the selected studies.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eGeneral trends in ESs assessments\u003c/h2\u003e \u003cp\u003eAssessments of ESs in coastal marshes were found in the literature already from 2009 with an increasing number of studies towards 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Regulating services dominated these assessments whilst cultural services were least investigated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Climate regulation was the most studied ES (i.e., 89 studies), followed by Bioremediation and water purification (60), services associated with Coastal protection (i.e., Flood Protection, Storm Protection and Erosion Control; a total of 50 studies) and Habitat maintenance (20; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Bioremediation and water purification dominated the services analyzed in the first decade of the 2000\u0026acute;s with a significant increase in the Climate regulation assessments from 2014 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Overall, temporal increases were observed in the number of studies assessing Climate regulation, Habitat maintenance, and Bioremediation and water purification, with less pronounced increases also evident for coastal protection\u0026ndash;related services. For the remaining regulating services, no clear temporal trends were observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). For provisioning services, food provision was the most assessed one with a slight increase in the number of studies from 2014 to 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). No temporal trends were observed for cultural services, with Recreation and Tourism, and Aesthetic values being the services most assessed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003eThe majority of studies (~\u0026thinsp;75%) analyzed only one ES (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). From the 185 studies selected for indicators extraction, only 23 adopted a mixed ESs perspective, also assessing components of the socio-economic system according to the Cascade model. Of these, 17 studies included monetary valuation of the assessed ESs, while the remaining six studies evaluated benefits in other ways (e.g., number of houses protected from floods or stakeholders\u0026rsquo; perceptions).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEcological indicators for ESs assessments\u003c/h3\u003e\n\u003cp\u003eThe number of indicators varied among the ESs assessed (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The highest number of indicators was found for Bioremediation and water purification whilst the lowest number occurred for Energy source. In general, Regulating services presented the highest numbers of indicators, parameters and co-indicators.\u003c/p\u003e \u003cp\u003eA high diversity of biogeophysical parameters and indicators was also identified throughout the distinct categories and services. In some cases, similar measurements were used across distinct ESs, although their role as parameters or indicators varied among services. For instance, soil accretion was applied as a direct indicator for Erosion control but served as a physical parameter in Bioremediation and ater purification and Climate regulation, where it was used to calculate sequestration rates (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Similarly, soil dry bulk density was a parameter for Bioremediation and water purification and Climate regulation, while functioning as a direct indicator for Hydrological cycle (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Some indicators also appeared as co-indicators, particularly Habitat area, which was used in almost all ESs analyzed. Habitat area was used solely to represent ES supply, but it was also an important measurement for upscaling other parameters typically measured at smaller spatial scales (e.g., denitrification rates, soil and plant carbon and nutrient content, soil elevation) and for ecological modelling (e.g., Exposure index, Carbon and Habitat quality models). ES values resulting from the combination of Habitat area with ES scores (i.e., numerical or categorical ratings of ESs; see Table S2) were also applied in the assessment of all services.\u003c/p\u003e \u003cp\u003eBioremediation and water purification, was assessed using a total of 23 indicators, including 4 co-indicators. From these, 9 indicators were calculated based on 19 biogeophysical parameters (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). Denitrification rates, nutrient stocks and sequestration rates were the most common ES indicators.\u003c/p\u003e \u003cp\u003eHabitat maintenance had 17 indicators supported by 8 biogeophysical parameters (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). Species diversity and habitat-related indices, such as Habitat quality models and ESs values (i.e., a combination of Habitat area with ES scores), prevailed among the indicators. Coastal protection-related services such as Erosion control, Flood protection and Storm protection had 8, 9 and 9 indicators, respectively (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec). Wave attenuation, Soil accretion, Surge attenuation and Exposure index, along with Habitat area, prevailed in these studies. A high number of biogeophysical measurements were observed (3, 15 and 10, respectively) for these coastal protection-related ESs. A similar trend was found for Climate Regulation (i.e., 24 measurements; Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed). Carbon stock was the most used indicator for Climate regulation, followed by carbon sequestration and greenhouse gas (GHG) fluxes. The remaining 8 regulating ESs presented a total of 17 indicators (including Habitat area, a co-indicator) with 14 biogeophysical parameters used to calculate them (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea). Habitat area was the prevailing indicator in Hydrological cycle, Soil quality, Ventilation and respiration and Microregional climate regulation.\u003c/p\u003e \u003cp\u003eA similar trend was observed for provisioning services (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea). The 5 provisioning services analyzed were investigated by using 13 indicators supported by 4 biogeophysical measurements plus an ES score (Figs., 6 and 8b). Habitat area prevailed as an indicator and was also the only co-indicator. For cultural services, 7 indicators were found of which 2 of them derived from 2 parameters (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec). Habitat area was the most used indicator and co-indicator for all services, except Religious and Spiritual values (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur study underscores the increasing recognition of the importance of coastal marshes for human well-being, a trend that likely reflects their growing relevance in addressing current environmental challenges. Despite this progress, there remains a clear need for more comprehensive, interdisciplinary research capable of translating the multiple ESs into effective management actions. By systematically reviewing the literature, our work broadens the range of parameters and indicators reported in previous reviews and highlights that employing bundles of indicators that integrate multiple ecosystem attributes is essential to adequately capture the complexity of coastal marsh ESs. Therefore, our findings offer a comprehensive toolbox and a valuable baseline for future assessments of ES supply in coastal marsh ecosystems.\u003c/p\u003e\n\u003ch3\u003eOverview of coastal marshes ESs assessments\u003c/h3\u003e\n\u003cp\u003eThe marked increase in ESs assessments of coastal marshes since 2009, as observed here, aligns with the rise in general ESs-related publications across terrestrial and aquatic habitats since then (Boerema et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), a trend also noted in assessments of coastal and marine ESs more broadly (Liquete et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e). The number of studies investigating ecosystem services in coastal wetlands, such as mangroves and seagrasses, has also increased since 2010, mostly reflecting their relevance for climate mitigation and coastal protection (Bimrah et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Lima et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Our findings confirm that, although coastal and marine ESs have historically received less attention than their terrestrial counterparts (Liquete et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e; De La Cruz, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), there has been growing recognition over the past decades of the vital role that coastal wetlands play in supporting human well-being.\u003c/p\u003e \u003cp\u003eRegulating services have received more attention than other ESs in marine and coastal literature (e.g., Liquete et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e), including seagrass and mangrove studies (Bimrah et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Lima et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and our findings reinforce this trend for coastal marshes. The low number of studies assessing Cultural services, on the other hand, corroborates previous findings that such ESs remain difficult to quantify and are understudied in marine and coastal areas (Liquete et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e; La Cruz, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We observed a shift in the most frequently assessed ESs over the study period, mirroring broader temporal trends reported for coastal wetlands (e.g., Cadier et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). During the 2000s, assessments focused largely on Bioremediation and water purification provided by coastal marshes, likely driven by efforts to mitigate eutrophication, which had become a widely recognized environmental concern by the 1980s and 1990s (Howarth and Marino, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In the 2010s, the emergence of climate change concerns and the Blue Carbon agenda, marked by seminal publications such as McLeod et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and Duarte et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), contributed to a surge in Climate regulation studies from 2014 onward (Costa and Macreadie, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Simultaneously, growing awareness of the value of coastal marshes in coastal hazard mitigation has fuelled assessments of coastal protection-related services (Erosion control, Flood regulation, and Storm protection services). A similar temporal pattern has been reported for coastal wetland restoration projects (e.g., Cadier et al., 2022), indicating that assessments of ESs in coastal marshes not only reflect evolving scientific and societal priorities but also align with shifts in research funding agendas over recent decades.\u003c/p\u003e \u003cp\u003eThe unique location of coastal marshes at the land-sea interface makes them a multifunctional system that simultaneously provides multiple ecosystem functions and services (Barbier et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Despite this, we found that most studies assessed only one or a few services, hence overlooking ESs bundles (i.e, co-occurring sets of ESs) and their potential synergies and trade-offs (Alemu et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Mason et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Reader et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). For instance, cattle grazing in coastal marshes may enhance Provisioning and Cultural services while negatively impacting Coastal protection, Habitat maintenance, and Climate mitigation (Davidson et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Graversen et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Marin-D\u0026iacute;az et al., 2021; Zhang et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, caution is needed to avoid the overrepresentation of certain ESs\u0026mdash;particularly those that are easier to quantify in monetary terms\u0026mdash;which can skew decision-making and undervalue other, less tangible but equally important services such as Spiritual and religious values, for instance (Boerema et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCoastal marshes\u0026rsquo; multifunctionality also entails economic and social benefits, as highlighted by frameworks such as the Cascade model. However, such frameworks are only useful if the full spectrum of the Cascade is investigated (La Notte et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Our findings indicate that only a small number of studies extended beyond the ecological realm of the framework, suggesting a disconnect between how coastal marshes function and how they are perceived and valued by society. Coastal marshes are often undervalued habitats, with limited public awareness of their societal benefits (Rendon et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; McKinley et al., 2020). Information on the ESs benefits derived from coastal marshes\u0026rsquo; ecological functioning can help bridge knowledge gaps and solve controversies between scientists and citizens. For instance, marsh restoration and conservation actions may re-establish some ESs, such as Storm protection, while limiting access to recreational activities. Clear communication of how ecological functioning underpins long-term benefits can ultimately foster societal support to management initiatives (Gaspers et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Grindsted et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In addition, monetary valuation of coastal habitats ESs provides a useful decision-support tool when properly used allowing these habitats to be included in decision-making frameworks and attracting funding for conservation and restoration (zu Ermgassen et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, despite the substantial increase in coastal wetland ESs assessments over the past decade, further efforts are needed by ecologists to effectively communicate human reliance on natural ecosystems. While striving to highlight ESs through quantification, we must also acknowledge that Nature\u0026rsquo;s existence value and intrinsic worth cannot be monetized. As Dasgupta (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) puts it in this review of the economics of biodiversity, \u0026ldquo;One may doubt, however, that hard-nosed cost-benefit analyses could be the right language in which to express all values. [..] but we do not put a price on the sacred. Our urge is simply to protect it.\u0026rdquo;\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eNumber of indicators\u003c/h2\u003e \u003cp\u003eBiogeophysical measurements of ecosystems is a fundamental step in estimating the provision of ESs and their associated benefits and costs (Grima et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In our analysis, Regulating services had the highest number of indicators, whereas Cultural services had the fewest. The indicators identified in this study align with those used to measure coastal protection-related services, carbon and nutrient dynamics, and primary and secondary production, reported in previous reviews on coastal wetland and marine systems (e.g., Shepard et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Liquete et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003eb\u003c/span\u003e; Cadier et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Nonetheless, our study expanded the number of parameters and indicators used, as well as the number of ESs evaluated, which may serve as a toolbox and baseline information for future coastal marsh ESs assessments.\u003c/p\u003e \u003cp\u003eThe high number of parameters and associated indicators observed for certain ESs may reflect methodological advancements, including the use of increasingly complex, process-based indicators and models. Frequently studied ESs, such as Bioremediation and water purification, Habitat maintenance, and Coastal protection-related services, often rely on indexes and ecological modelling, which explains the high number of both parameters and indicators associated with these services. For instance, whilst services such as Erosion Control and Storm protection tend to be assessed through straightforward measurements of soil accretion/elevation and wave attenuation, respectively, Flood protection often relies on the use of more complex measurements and modelling, as also noted by Shepard and collaborators (2011). Additionally, certain Regulating ESs are composed of multiple components, further contributing to indicator diversity (Boerema et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Indicators of Bioremediation and water purification often encompass various stages of nitrogen cycling (e.g., nitrification, denitrification) across different environmental compartments, including the water column, porewater, and soils. On the other hand, a high diversity of indicators may also reflect a lack of methodological consistency for certain ESs, potentially hindering comparisons across studies (Cadier et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe low number of indicators identified for services such as Climate regulation and Coastal protection-related studies suggests a high degree of consensus in their assessments. Accordingly, efforts to standardize sampling protocols and analytical approaches within the Blue Carbon research community in the last decade (e.g., Costa and Macreadie, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Dahl et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, few studies assessed both carbon sequestration and GHG emissions (here named C budget), thereby providing a more comprehensive view of the climate benefits provided by coastal marshes (Dahl et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Williamson and Gattuso, 2022; Kristensen et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Indeed, measurements of GHG fluxes in coastal wetlands are still scarce in the literature, especially if compared with Blue Carbon sequestration assessments (Cadier et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similar patterns were observed for other services, such as Bioremediation and water purification, and Habitat maintenance, where methodological consistency (i.e., the predominant use of a few indicators) was not always accompanied by comprehensive assessments of service components. Therefore, achieving both methodological consistency and ecological comprehensiveness in the use of indicators remains a key challenge in the assessment of coastal marsh ESs. In this sense, we suggest that using bundles of indicators is necessary to fully capture the complexity and functioning of ESs provided by coastal marshes.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTypes of indicators\u003c/h3\u003e\n\u003cp\u003eThe use of appropriate indicators is essential for accurately assessing ESs and several ecosystem attributes such as diversity, structure, and function have been employed for this purpose (Broszeit et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Egoh et al., 2012; Ruiz-Jaen and Aide, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). For provisioning services, structural indicators such as habitat area, annual catch, and yield (both annual and areal) were predominant, supporting the relevance of structural attributes in evaluating this service category (La Notte et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Regulating services, in turn, were more often assessed using functional indicators (e.g., carbon and nutrient fluxes, erosion control, and wave attenuation) derived from biogeochemical parameters and statistical modeling of interactions between biotic and abiotic components. However, we observed that several Regulating services are still commonly assessed using indicators that reflect ecosystem properties (e.g., carbon and nutrient stocks) rather than ecosystem functions (e.g., carbon and nutrient accumulation rates. While stock measurements provide insights into the potential capacity of an ecosystem to supply a service, they do not account for the temporal scale and dynamics in the functions providing ESs (Boerema et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cadier et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Garland et al., 2020).\u003c/p\u003e \u003cp\u003eThe use of Habitat area as an indicator underscores the growing role of remote sensing in ESs mapping and monitoring, as it provides spatially explicit, consistent, and repeatable data across large areas and timeframes (Grima et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, and references therein). However, the widespread use of Habitat area as a single indicator of Provisioning and Cultural services, but also some Regulating ones, can lead to over- or underestimation of actual ESs provision (Schr\u0026ouml;ter et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In coastal marshes, ESs provision varies with factors such as species composition, tidal dynamics, geomorphology, and soil characteristics (e.g., Duarte et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Leivas-Due\u0026ntilde;as et al., 2024; Spencer and Harvey, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), which are not captured by areal estimates alone. Nonetheless, if combined with other functional parameters measured at smaller spatial scales (e.g., m\u003csup\u003e2\u003c/sup\u003e), Habitat area can be an important indicator allowing upscaling ESs provisions to the habitat level. Indeed, we found that for most ESs investigated, spatial modeling often incorporated Habitat area, a structural metric, as a parameter combined with functional attributes to map coastal marshes' ESs provision. Tools like InVEST (Natural Capital Model, 2025) integrate habitat area with biophysical data to model changes in ESs provision driven by land-use change, enabling scenario analyses for conservation and land management (Meraj et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The reliability of such models depends heavily on parameterization and calibration with local data derived from field measurements or literature to ensure accurate outputs (Meraj et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Peh et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Schr\u0026ouml;ter et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), hence highlighting how ESs assessments can benefit from combining different ecosystem attributes (Ruiz-Jaen and Aide, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur findings provide important insights regarding the use of ecological indicators in coastal marsh ESs assessments However, many ecological studies, do not explicitly frame their findings within the ESs framework and/or were performed before the concept was coined, a pattern previously observed in reviews for seagrasses (e.g., Ruiz-Frau et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and salt marshes (e.g., Shepard et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In many cases, the term ES is only mentioned in the Discussion section or is not mentioned at all, limiting our ability to identify such studies through conventional database searches using titles, abstracts, and keywords. We hence acknowledge that a substantial body of ecological literature on the functioning of coastal marsh habitats that could be translated into ESs assessments was not present in our analysis; however, including all those studies would make the systematic review unfeasible. Despite these limitations, we are confident that our analysis captures, if not all, most of the ecological indicators currently applied in coastal marsh ESs assessments.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe present study indicates that although significant progress has been made in assessing coastal marshes\u0026acute; ESs in the last decades, some challenges persist. Regulating and Provisioning services are better characterized in coastal marshes, whilst Cultural services are still understudied, limiting comprehensive assessments of ESs synergies and trade-offs. The few interdisciplinary assessments, combined with the predominance of single-service evaluations, also indicates that the ESs provided by coastal marshes may be inadequately conveyed to stakeholders and insufficiently integrated into coastal management strategies. Future studies should be conducted by interdisciplinary groups and consider the full range of ESs provided by coastal marshes to better inform coastal management. Assessments of coastal marsh ESs should preferably use bundles of complementary ecological indicators, as single indicators are typically insufficient to capture the complexity of ESs. Importantly, such a multivariate approach must encompass not only several indicators but also distinct ecosystem attributes, including functional ones. Finally, managers would benefit if ecological studies would be explicitly framed into the ESs concept, thereby enhancing the translation of ecological findings into monetary and societal benefits to support informed decision-making.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eCompeting interest\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was part of the NordSalt project funded through the 2019\u0026ndash;2020 BiodivERsA joint call for research proposals, under the BiodivClim ERA-Net COFUND programme, and with the funding organisations: Innovation Fund Denmark (ID), The Academy of Finland (AKA), German Research Foundation (DFG), The Research Council of Norway (RCN), and The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS).\u003c/p\u003e\u003ch2\u003eAuthors\u0026rsquo; contributions:\u003c/h2\u003e \u003cp\u003e \u003cb\u003eML\u003c/b\u003e: Conceptualization, Data curation, Investigation, Methodology, Formal analysis, Visualization, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. \u003cb\u003eGOF\u003c/b\u003e: Conceptualization, Data curation, Investigation, Methodology, Validation, Writing \u0026ndash; review \u0026amp; editing. \u003cb\u003eAV\u003c/b\u003e: Methodology, Writing \u0026ndash; review \u0026amp; editing. \u003cb\u003eCB\u003c/b\u003e: Writing \u0026ndash; review \u0026amp; editing. \u003cb\u003eDKJ\u003c/b\u003e: Writing \u0026ndash; review \u0026amp; editing. \u003cb\u003eKJ\u003c/b\u003e: Writing \u0026ndash; review \u0026amp; editing. \u003cb\u003eCOQ\u003c/b\u003e: Conceptualization, Writing \u0026ndash; review \u0026amp; editing. \u003cb\u003eGB\u003c/b\u003e: Conceptualization, Funding acquisition, Methodology, Validation, Supervision, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe are grateful to Thea Marie Drachen, from the library of the University of Southern Denmark, for assistance with the databases searches.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdam, P. 1990. \u003cem\u003eSaltmarsh Ecology\u003c/em\u003e. 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Ecosystem Services: Delivering Decision-Making for Salt Marshes. \u003cem\u003eEstuaries and Coasts\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(6), 1691\u0026ndash;1698. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12237-021-00952-z\u003c/span\u003e\u003cspan address=\"10.1007/s12237-021-00952-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"estuaries-and-coasts","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esco","sideBox":"Learn more about [Estuaries and Coasts](https://www.springer.com/journal/12237)","snPcode":"12237","submissionUrl":"https://www.editorialmanager.com/esco/","title":"Estuaries and Coasts","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Cascade model, multifunctionality, ecosystem attributes, multivariate approach, CICES, proxies","lastPublishedDoi":"10.21203/rs.3.rs-8864533/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8864533/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCoastal marshes are heterogeneous habitats that provide multiple ecosystem services (ESs) but have suffered major declines on the global scale. Therefore, the conservation and restoration of marshes are pivotal for biodiversity maintenance and climate change mitigation and adaptation. However, the evaluation of their effectiveness to tackle environmental challenges depends on ESs assessments grounded in ecological indicators, for which comprehensive, updated overviews are lacking. We systematically reviewed the ecological literature to identify the temporal evolution of coastal marsh ESs assessments, along with the diversity and operationalization of ecological indicators. We found that studies on coastal marsh ESs have grown since 2009, with a predominance of research on Climate Regulation, Bioremediation/Water Purification, and Coastal protection-related services. Most studies focused on a single service, overlooking potential synergies and trade-offs among ESs. Furthermore, few ecological studies evaluated social or economic benefits, indicating challenges in effectively communicating human reliance on coastal marshes. The number and type of ecological indicators varied across services. A high diversity of indicators reflected both the maturity of certain ESs and a lack of standardized metrics, indicating that methodological consistency and ecological comprehensiveness remain a challenge. We highlight that multivariate approaches, assessing multiple ESs by using bundles of complementary indicators, will enable more informative assessments. This study provides guidance for selecting appropriate ecological indicators and underscores the need to integrate ecological, social, and economic dimensions of coastal marsh ESs to better support management and policy strategies.\u003c/p\u003e","manuscriptTitle":"Assessing Coastal Marshes Ecosystem Services: A Systematic Review of Ecological Indicators","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-24 08:00:01","doi":"10.21203/rs.3.rs-8864533/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2026-02-23T15:07:57+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-19T17:06:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-13T03:38:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Estuaries and Coasts","date":"2026-02-12T13:52:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"estuaries-and-coasts","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esco","sideBox":"Learn more about [Estuaries and Coasts](https://www.springer.com/journal/12237)","snPcode":"12237","submissionUrl":"https://www.editorialmanager.com/esco/","title":"Estuaries and Coasts","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0cbac764-3dd7-4984-b489-4b2023573698","owner":[],"postedDate":"February 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T14:56:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-24 08:00:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8864533","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8864533","identity":"rs-8864533","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}