The development of the System of Environmental Economic Accounting - Ecosystem Accounting (SEEA EA, United Nations et al. 2021) promotes empirical applications to understand the contribution of the environment to the economy and human activities. Marine ecosystems contribute to the so-called Marine-Based Tourism (MBT), which represents a form of tourism, based on enjoying recreational opportunities related to the marine and coastal environment.

Despite the link between ecosystem quality and tourism demand being well-recognised, the contribution of marine and coastal ecosystems to the tourism sector is complex and challenging to isolate for accounting purposes. However, the predominant interest in the Blue Economy and the Biodiversity COP15 commitments should prioritise this analysis. This paper addresses this urgency by proposing the first ecosystem service account for MBT in Italy.

In 2019, the EU Blue Economy Observatory reported that the MBT sector generated a Gross Value Added (GVA) of €81.5 billion (European Commission et al. 2023). Nature Conservancy’s Mapping Ocean Wealth (2017) shows that coral reefs worldwide contribute significantly to global tourism, generating 70 million trips annually and a substantial economic value of $36 billion each year, of which $19 billion stems from direct “on-reef” tourism activities (e.g. diving, glass-bottom boating, wildlife observation within the reef). MBT significantly influences also local economies (Visintin et al. 2022, Gupta et al. 2023), which are encouraged to promote activities, based on the marine environment, such as whale watching, recreational fishing and diving (O’Connor et al. 2009; Cisneros-Montemayor et al. 2020; Gonzáles-Mantilla et al. 2022).

The availability, quality and accessibility of natural resources have recently gained a significant role in the choice of tourist destinations and activities (Otrachshenko and Bosello 2017). Marine recreation opportunities are intricately linked to the presence of ecosystems, such as coralligenous habitats (Spalding et al. 2017, Tonin 2018), seagrass habitats (Zunino et al. 2020) and specific coastline features, such as rocky reefs (Cardoso-Andrade et al. 2021). At the same time, marine ecosystems’ deterioration negatively affects both tourist arrivals, i.e. the number of customers who checked in at a country's accommodation during a given period (ISTAT 2024, https://noi-italia.istat.it/) and the length of stay with consequent economic losses (Bigano et al. 2007, Onofri and Nunes 2013).

Therefore, understanding the impact and dependency of MBT on marine and coastal ecosystems is crucial policy decision information and the SEEA EA represents an accounting framework that can facilitate this process.

The paper contributes to account for the relationship between marine ecosystems and socio-economic data to identify the role of Posidonia Oceanica in the tourism demand in Italian coastal areas. We provide the first MBT ecosystem account in biophysical and monetary terms to emphasise the urgency for collecting, organising and improving the mapping and monitoring of marine ecosystems. The paper is structured as follows: Previous works summarises previous works aimed at identifying the economic contribution of ecosystems to the tourism sector and introduces MBT in an accounting context. Data collection and methods explains the method and data used referring to: i) identification, quantification and mapping of P. Oceanica; ii) quantification of the biophysical flow of the service provided; iii) conversion of the flow into monetary terms. The empirical results are described in Results section, while Concluding remarks concludes.

Given the broad set of benefits gained from marine ecosystems, such as fish and biomass as provisioning ecosystem services (ES), carbon storage and sequestration and coastal protection as regulating ES and recreational opportunities as cultural ES, literature related to the economic Monetary valuation of such services is very diversified. However, previous works that focus on the contribution of ecosystems to the economy are limited. Furthermore, it is worth noting that MBT refers primarily to tourism flows and differs from daily recreation activities. Although this distinction is crucial for ecosystem accounting (see Vallecillo et al. (2019), Zulian and La Notte (2022)), this clarification is often missing in previous papers.

Most of the previous studies focus on specific marine activities, such as whale watching (O’Connor et al. 2009), recreational fishing (Cisneros-Montemayor et al. 2020), shark watching (Gallagher and Hammerschlag 2011) and diving (Rodrigues et al. 2016, Chimienti et al. 2017, Gonzales-Mantilla et al. 2022). Studies that investigate the impacts of MBT activities on the economy (O’Connor et al. 2009, Cisneros-Montemayor et al. 2020) rely upon Input-Output (IO) or Social Accounting Matrix (SAM) coupled with tourist expenditure surveys to estimate value-added impacts (Chidakel et al. 2021), but without analysing the role of marine ecosystems.

Other studies assess marine cultural services, such as aesthetic and seascape value and underwater cultural heritage sites (Manglis et al. 2020). However, none of these previous studies is suitable for ecosystem accounting purposes where the main aim is to attribute the marine contribution to tourism flows.

Fewer papers clarify their intention to contribute to ecosystem accounts, considering mainly daily recreation activities of terrestrial ecosystems (Fitch et al. 2022, Zulian and La Notte 2022) or specific marine ecosystems. Fitch et al. (2022) investigated the contribution of national parks and coastal areas to tourism expenditure in the UK, finding that the contribution of natural capital in 2017 was equivalent to 0.4% of the UK GDP. Zulian and La Notte (2022) have used an INCA-based methodology (the Integrated System for Natural Capital Accounts project launched by the European Commission in 2015) to analyse the contribution of nature to tourism in four Italian regions. The study focuses on the role of terrestrial ecosystems (settlements, cropland, woodland and forest, wetland), including the broad category of water (related to sea and freshwaters), to attract tourists. Their results show that 56.69% (246 million) of the overnight stays were motivated by nature-based tourism. Our approach expands these previous studies to assess the MBT motivated by the presence of the P. oceanica seagrass ecosystem in Italian regions.

P. oceanica is an endemic Mediterranean seagrass recognised for its ecological importance and the ecosystem services it provides (Catucci and Scardi 2020). It plays a crucial role in biodiversity conservation, sediment stabilisation and carbon sequestration and serves as a habitat and food source for various marine organisms (Bidak et al. 2021). The assessment of P. oceanica is prioritised over other species due to its status as a keystone species within its habitat, its sensitivity to environmental changes and its function as a biological indicator of the health of marine ecosystems (Tursi et al. 2021, Mutlu et al. 2024). P. oceanica is also used as a "biological quality element" for monitoring activities of marine species and habitats of Directives 92/43/EC "Habitats" and 2009/147/EC "Birds" provided for by the DM 11/2/2015 implementing of Article 11 of Legislative Decree 190/2010 (Marine Strategy). Furthermore, the economic Monetary valuation of ecosystem services provided by P. oceanica highlights its significant contribution to human well-being, further justifying the focus on this species (Campagne et al. 2015). In summary, assessing and monitoring P. oceanica is imperative to provide information for conservation efforts and ensure the sustainability of Mediterranean marine ecosystems.

This work focuses on assessing the Marine-Based Tourism (MBT) ecosystem service provided by P. oceanica. Our approach involves three primary steps, as illustrated in Fig. 1. The first is determining the extent and condition of P. oceanica. It follows the biophysical quantification of the ES flow and the conversion of this flow into monetary terms. The second one involves the biophysical quantification of the ecosystem service, while the third consists of converting the physical flow into monetary terms.

Figure 1.

Steps to assess the marine-based tourism ES provided by the P. oceanica.

Biophysical quantification of Posidonia oceanica extent and condition

The first step, consistent with the SEEA EA, aims to determine the extent and condition of the Italian P. oceanica meadows. Despite the importance of this ecosystem, data on P. oceanica meadows in Italy are notably scarce, outdated or completely absent. Therefore, the first step is to statistically reconstruct a reliable dataset from the available data illustrated in Table 1.

Table 1.

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Scope of datasets used in the analysis

Dataset	Available at	Scope
EUSeamap 2021	https://emodnet.ec.europa.eu/en/seabed-habitats	Extent of Italian P. oceanica meadows.
Italian administrative boundaries	https://www.istat.it/it/archivio/222527	Administrative boundaries of Italian municipalities
Monitoring data under the Marine Strategy Framework Directive	http://www.db-strategiamarina.isprambiente.it/app/#/datiMonitoraggio20182023	Density of the meadows in the sampled area

To derive the extent of meadows, we refer to EUSeamap 2021 (Vasquez 2021, accessed in July 2023) and use QGIS software to extract meadows that meet the following criteria simultaneously: i) the 2007-2011 EUNIS code was “A5.535: [Posidonia] beds”; ii) the 2019 EUNIS code was “MB252: Biocenosis of [Posidonia oceanica]”; iii) the substrate type was “[Posidonia oceanica] meadows” and iv) they were located within Italian administrative boundaries. EUSeaMap is a comprehensive predictive seabed habitat map developed through the EMODnet Seabed Habitats project, which involves biologists and seabed habitat mapping experts. The project aims to map and predict seabed habitats, enhancing marine spatial planning and conservation efforts. Seabed habitat maps are available to inspect on the project website (https://emodnet.ec.europa.eu/geoviewer/), allowing the download of map shapefiles.

Subsequently, P. oceanica meadows are linked to each Italian coastal municipality to facilitate the connection between the biophysical and monetary Monetary valuation steps. We use biophysical monitoring data from ISPRA (https://strategiamarina.isprambiente.it/sic-sistema-informativo-centralizzato/), collected under the Marine Strategy Framework Directive to assess the condition of the habitat. The dataset includes information about the density, i.e. the number of P. oceanica shoots/m², which can be considered a proxy indicator of the health status of P. oceanica (Montefalcone 2009) within the sampled sites across different time ranges (1999-2011 and 2018-2021). In each municipality, we can have null, one or multiple observations of P. oceanica density over time. In the latter case, we aggregate the information and compute the average density at the municipality level. However, density data are unavailable for all years or for municipalities where P. oceanica is present. To address this limitation, as IDEEA Group (2020) suggests, we apply two types of interpolation: temporal and spatial. These techniques produce estimates of average P. oceanica density in each coastal municipality for all relevant years. Fig. 2 provides an overview of the steps taken to estimate the extent and condition of the P. oceanica ecosystem.

Figure 2.

Steps to assess the extent and condition of P. oceanica Italian meadows, dataset used and applied methodologies.

First, a fixed-effect ordinary least squares model using available yearly observations and a spatial identifier (geo) generated using the geohashTools package (https://www.rdocumentation.org/packages/geohash/versions/0.3.0) permits capturing site-specific characteristics. Predicted density values for missing years are then generated using the estimated coefficients.

For spatial interpolation, we run a second model regressing the density (observed or predicted) on the year, latitude, longitude and concentrations of phosphorus and nitrogen (proxies for anthropogenic pressure on marine ecosystems, aggregated from Grizzetti et al. (2021). Coefficients from this model are used to predict density in municipalities that are not monitored, resulting in observed or predicted values, based on the interpolation type. Through these temporal and spatial regressions, we establish the condition of P. oceanica in each municipality.

Tourism dependency on P. oceanica - ecosystem service flow in physical terms

Monetary valuation - ecosystem service flow in monetary terms

In this section, we present the key outcomes of each stage in our analysis: i) the assessment of P. oceanica extent and condition, ii) the estimates from models used to identify the portion of the tourism flow attributable to the P. oceanica ecosystem and iii) the conversion of this flow into monetary terms. Additionally, we present the supply and use tables (SUT) for the MBT ecosystem service provided by P. oceanica in Italy in both physical and monetary terms for 2019 and 2021. We selected these two years because: i) they are the most recent and ii) they are the only two years in which we have all the available information (i.e. population and tourism statistics).

Extent and condition of P. oceanica

Table 3 shows the extent and condition of P. oceanica meadows in Marsala Municipality, located in Sicily, as an example. The extension of meadows has been aggregated at the municipality level and density has been estimated by the temporal and spatial interpolation described in Biophysical quantification of Posidonia oceanica extent and condition section. Models’ estimates are available in the supplementary material (Suppl. material 1).

Table 3.

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Extent and condition (density) of P. oceanica Italian meadows for the Marsala Municipality.

Municipality	ISTAT code	Extent (m2)	Year	Observed density (shoots/m2)	Predicted density (shoots/m2)
Marsala	81011	80152829.64	2014	-	269.848 [165.459, 372.707]
			2015	-	265.031 [160.519, 369.025]
			2016	-	260.213 [155.403, 364.398]
			2017	-	255.396 [150.439, 359.361]
			2018	361.6	361.6
			2019	-	245.760 [139.391, 350.555]
			2020	-	240.942 [134.509, 346.508]
			2021	84	84
Note: 95% confidence intervals for the predicted values are estimated via 10000 Monte Carlo simulations and reported in brackets.

Fig. 3 and Fig. 4 show the density maps of P. oceanica meadows in the same area in 2019 and 2021, respectively. The maps show the decreasing trend of the P. oceanica density estimated from the models.

Figure 3.

Predicted density of P. oceanica meadows in the Municipality of Marsala in 2019.

Figure 4.

Predicted density of P. oceanica meadows in the municipality of Marsala in 2021.

Ecosystem service flow in physical terms

Ecosystem service flow in monetary terms

This study represents the first Italian Marine-Based Tourism ecosystem account, offering insights into the complexity of assessing its physical and monetary flows. The interest in empirical applications and the development of ecosystem accounts under the SEEA EA framework is exponentially growing. Within this framework, we propose a methodological and empirical approach to estimate the role of marine ecosystems in the marine-based tourism sector. We show in three main steps how the employment of biophysical and socio-economic information in a statistical model allows us to: i) assess the contribution of the marine ecosystem to the tourism sector in physical and monetary terms and ii) fill the use and supply tables required in ecosystem accounting.

The proposed approach allows us to estimate the value of the contribution of MBT provided by P. oceanica to the tourism industry by using travel expenditure. We find that P. oceanica significantly contributes to the tourism sector, resulting in exchange values of MBT of €6 million in 2019 and €3.7 million in 2021.

Our findings contribute to a clearer understanding of MBT from an accounting perspective. Marine ecosystems, here proxied by P. oceanica, provide direct or indirect ecosystem services. In the MBT, this role is “indirect” because P. oceanica density is used as a proxy to determine the number of touristic arrivals due to the good quality of coastal habitats. However, the economic benefits are quite substantial and a loss of ecosystem extent and conditions can impact the tourism sector.

Despite the progress made in this analysis, there is still room for methodological and empirical improvements, mainly related to mapping marine ecosystems and data availability. Data availability particularly affects our biophysical assessment. While the temporal model works fine, the spatial model is subject to greater limitations, mainly due to the limited availability and fragmented nature of data on the condition of Italian marine ecosystems. A series of other variables could be included in the model to represent the anthropogenic pressure on the ecosystem. For example, including other variables on recreational boat anchorages, water turbidity and sediment quality might represent a significant opportunity to improve the model and, consequently, the accuracy of the estimates, which, however, already provide starting data for the development of the related accounting tables. In this context, we emphasise the urgent need for improved data availability. Collection, organisation, updating and accessibility are key to compiling accurate and complete accounts of marine ecosystems.

Nevertheless, this paper provides valuable insights for policy-makers to expand their options of actions related to the nature-based tourism sector. By carefully reading the information from the supply and use tables of ecosystem accounting, policy-makers can plan investments orientated towards monitoring, conservation or restoration of marine ecosystems considering the impact on the tourism industry and relying on a broader, more comprehensive set of information (e.g. their geographical area, physical and monetary accounts).

*Valentina di Gennaro worked on this study in the framework of the MARBEFES (MARine Biodiversity and Ecosystem Functioning leading to Ecosystem Services) project, funded by the European Union under the Horizon Europe Programme, “HORIZON-CL6-2021-BIODIV-01” Theme, Grant Agreement no. 101060937 [marbefes.eu]. The work of Alice Bartolini was co-founded by the European Union - FSE REACT-EU, NOP Research and Innovation 2014-2020.

ISPRA - Istituto Superiore per la Protezione e la Ricerca Ambientale (Institute for Environmental Protection and Research), within the context of the project "Servizio di elaborazione di dati e informazioni biofisiche finalizzare alla contabilizzazione dei servizi ecosistemici marini", resulting from the collaboration between ISPRA and the Department of Political and International Sciences of the University of Siena.

Alessio Capriolo and Silvia Ferrini planned and supervised the project. Silvia Ferrini and Alessandra La Notte designed the study. Alice Bartolini, Vittoria Reas and Valentina Di Gennaro collected data and conducted the analysis. All co-authors contributed to the writing of the article.