European SMEs' exposures to ecosystems and natural hazards: A first exploration

Fatica, Serena; Grammatikopoulou, Ioanna; Hirschbühl, Dominik; La Notte, Alessandra; Pisani, Domenico Working Paper European SMEs' exposures to ecosystems and natural hazards: A first exploration JRC Working Papers in Economics and Finance, No. 2024/3 Provided in Cooperation with: Joint Research Centre (JRC), European Commission Suggested Citation: Fatica, Serena; Grammatikopoulou, Ioanna; Hirschbühl, Dominik; La Notte, Alessandra; Pisani, Domenico (2024) : European SMEs' exposures to ecosystems and natural hazards: A first exploration, JRC Working Papers in Economics and Finance, No. 2024/3, European Commission, Ispra This Version is available at: https://hdl.handle.net/10419/299594 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ European SMEs’ exposures to ecosystems and natural hazards: a first exploration Fatica, S. Grammatikopoulou, I. Hirschbuehl, D. La Notte, A. Pisani, D. 2024 JRC Working Papers in Economics and Finance, 2024/3 This publication is a Working Paper by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. It aims to provide evidence-based scientific support to the European policymaking process. Working Papers are prepublication versions of technical papers, academic articles, book chapters, or reviews. Authors may release working papers to share ideas or to receive feedback on their work. This is done before the author submits the final version of the paper to a peer reviewed journal or conference for publication. Working papers can be cited by other peer-reviewed work. The contents of this publication do not necessarily reflect the position or opinion of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication. For information on the methodology and quality underlying the data used in this publication for which the source is neither Eurostat nor other Commission services, users should contact the referenced source. The designations employed and the presentation of material on the maps do not imply the expression of any opinion whatsoever on the part of the European Union concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Contact information Name: Dominik Hirschbuehl Address: Joint Research Centre, Via Enrico Fermi 2749, I-21027 Ispra (VA), Italy Email: [email protected] Tel.: +39 0332 78 6328 EU Science Hub https://joint-research-centre.ec.europa.eu JRC136901 Ispra: European Commission, 2024 © European Union, 2024 The reuse policy of the European Commission documents is implemented by the Commission Decision 2011/833/EU of 12 December 2011 on the reuse of Commission documents (OJ L 330, 14.12.2011, p. 39). Unless otherwise noted, the reuse of this document is authorised under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence (https://creativecommons.org/licenses/by/4.0/). This means that reuse is allowed provided appropriate credit is given and any changes are indicated. For any use or reproduction of photos or other material that is not owned by the European Union, permission must be sought directly from the copyright holders. How to cite this report: European Commission, Joint Research Centre, Fatica Serena, Grammatikopoulou Ioanna, Hirschbuehl Dominik, La Notte Alessandra, Pisani Domenico, European SMEs’ exposure to ecosystems and natural hazards: a first exploration, European Commission, Ispra, 2024, https://publications.jrc.ec.europa.eu/repository/handle/ JRC136901, JRC136901. Executive summary This article explores the vulnerability of European small and medium-sized enterprises (SMEs) to ecosystem services and natural hazards, and, the possible implications for financial stability. The focus on SMEs is motivated by the fact that environmental degradation and natural hazards are likely to be especially disruptive for smaller firms since they lack geographically diversified business operations and as they have limited capacity to share risk within business groups or via capital markets. The analysis uses the Encore (Exploring Natural Capital Opportunities, Risks and Exposure) framework, which is widely used in the financial community for assessing nature-related risks. The framework transparently provides materiality ratings for different ecosystem service dependencies and impacts on various economic sectors. For instance, it identifies the dependency of a specific industry on groundwater, which is directly applicable to a firm operating in that industry. In addition, geospatial information can help to investigate whether a firm is operating in a region where groundwater is under stress. This may imply that production is at risk. Ecosystem dependencies reflect the fact that the economy or a firm benefits from using ecosystem services for its production process, either as direct inputs or as protection from disruption, and this firm may be subject to vulnerabilities stemming from a disruption of those. Every ecosystem dependency has a corresponding climate physical risk or hazard (flood protection – flood risk, soil retention – soil erosion risk, water - drought). In this study, we focus on two regulating ecosystem services relevant to economic activities: soil retention and flood protection. In addition, we explore a material service using measures of water provisioning. In addition, the role of soil erosion risk, flood risk and droughts is investigated. The analysis indicates that there are moderate direct risks under current conditions for a large part of SMEs. For instance, among agricultural SMEs, about 9% of all firms are highly reliant on the ecosystem service soil retention and are subject to significant regional ecosystem stress and soil erosion risk, requiring them to buy additional fertilizer to oppose degrading soil fertility. For the case of water, according to a holistic mapping 27.9% of debt belongs to companies who are highly reliant on surface water ecosystems. 9% of this debt operates in regions that experiences seasonal water stress as measured by an augmented water exposure index. Both ecosystem provisioning shortages and natural hazards tend to be regionally concentrated, potentially adversely affecting companies' operations and locally operating banks in some regions. While at the current stance nature physical risks appear comparatively muted, changing climatic conditions and non-sustainable use of ecosystem services might intensify risks over the next decade, potentially impacting the operations of companies and locally operating banks in those areas. The current findings are a first assessment based on rough estimates that need further refinement. More research is required to enhance the precision and ensure the suitability of some variables for sustainability assessments, especially in economic or financial contexts. At the current stance, due to regional concentration of some metrics, an unconditional application could disadvantage peripheral regions where economies might be sustainable despite contrary indicators. The study could also benefit from considering additional ecosystem services, like soil quality and water purification. Moreover, the framework should explore the effects of potential ecosystem degradation or increased natural hazards under future climate change scenarios. Developing reliable short-term forecasts for these factors could enhance risk analysis and develop models to understand the escalation potential of nature physical risks in the near term. European SMEs’ exposure to ecosystems and natural hazards: a first exploration∗ Serena Fatica, Ioanna Grammatikopoulou, Dominik Hirschb¨uhl, Alessandra La Notte, Domenico Pisani Version March 10, 2024 Abstract Nature-related financial risks have emerged as critical concerns for policymakers and financial actors. Central to this issue are ecosystem services, which play an integral role in various production processes but may be interrupted due to nature degradation. This article delves into the vulnerability of European SMEs by combining firm-level exposures to ecosystem service dependencies with regional information on the relative abundance of ecosystem services provisioning and the risk of natural hazards. Focusing on long-term debt positions to gauge financial stability implications, the results reveal moderate nature risks for European SMEs at the current stance but also highlight a possible concentration of risks and a need to further refine the use of available indicators. Keywords: ecosystem services, natural capital, nature degradation, physical risks, environmental risks, ENCORE, risk management, SMEs. JEL Codes: G21, G38, Q5. ∗Corresponding author: Dominik.Hirsch[email protected]. European Commission, Joint Research Centre, Via E. Fermi 2749, 21027 Ispra (VA), Italy. We are grateful for the helpful comments provided by Joachim Maes, Panos Panagos, Yanni Trichakis and some anonymous referees. Disclaimer: The content of this article does not necessarily reflect the official opinion of the European Commission. Responsibility for the information and views expressed therein lies entirely with the authors. 1 Introduction Developing a better understanding of nature-related financial risks has become a focal point for policymakers, the financial community, and regulators. This is because economic activities are intrinsically linked to the health of natural ecosystems, which provide, for instance, material and regulating services such as direct physical inputs (e.g. water) for production or protection from natural hazards (e.g. floods). Consequently, ecosystem degradation can be a source of production disruptions, potentially posing significant risks to economic growth and financial stability. This study proposes a more comprehensive view of nature risks by refining pure ecosystem-service exposures with regional conditions of ecosystem services provision. While a relation between nature and economic activities is undisputed, it is not immediately clear why and how ecosystem services relate to production processes. For this, we start with a definition of what constitutes an ecosystem. According to the Convention on Biological Diversity1, an ecosystem is defined as “a dynamic complex of plant, animal and micro-organism communities and their non-living environment interacting as a functional unit.” Ecosystems can be terrestrial (land-based) and aquatic (water-based). They comprise nonliving (abiotic) elements, such as, for instance, minerals, climate, soil, water, sunlight, and living (biotic) elements. Ecosystems face natural disturbances, such as variations in temperature and precipitation or wildfires, and pressures from economic activities, particularly polluting ones, but also overuse or land transformations. All in all, these non-sustainable practices can disrupt ecosystems, leading to imbalances and irreversible alterations. In turn, poorly maintained ecosystems provide less effective protection against natural hazards and fewer direct physical inputs than needed, resulting in unmet demand. Analyses that provide insight into how degrading ecosystems and natural hazards affect economic growth and financial stability are advancing rapidly (for instance, see Carvalho et al.,2022;Boldrini et al.,2023). Yet, research to integrate those and understand the broader consequences for the financial system and the entire economy is still in its infancy. Advancing quantitative capacities is warranted as a first step to identify the many facets 1see Convention on Biological Diversity, accessed on February 2024: https://www.cbd.int/convention. 1 of the problem and mainstream the consideration of nature-related risks into economic and financial decision-making. Similarly, international institutions at the global level are increasing efforts to reach a common language and a transparent approach to conceptualise and measure nature-related risks (OECD,2023;NGFS,2023;ECB/ESRB,2023). Against this background, the European Commission put forward a comprehensive longterm plan, the so-called Biodiversity Strategy 20302with specific actions and commitments to protect nature and reverse the degradation of ecosystems. Among the many actions, the strategy envisages, for instance, the creation and expansion of protected areas on land and sea, and a nature restoration plan. In addition, the objectives of the EU water policy3 foresee ensuring access to good quality water in sufficient quantity for all Europeans, economic sectors and the environment. It also intends to ensure the good state of European water bodies by moving towards a water-efficient and water-saving economy. From a technical point of view, water scarcity results from temporary or spatial water mismanagement, leading to a state where supply cannot cover anthropogenic and environmental demand. In addition, in July 2023, the EU proposed a new Soil Monitoring Law4to protect and restore soils and ensure their sustainable use. While these actions may improve the long-run health of ecosystems, they may impose constraints on current economic activity. This study is a first attempt to offer a thorough understanding of nature-related risks faced by small and medium-sized European enterprises (SMEs) that extends beyond the level of exposure. To achieve this, it uses firm-level exposures (sector-level approximation) for ecosystem dependencies provided by the Encore (Exploring Natural Capital Opportunities, Risks and Exposure) framework as described in Natural Capital Finance Alliance (2022) (see section 2) and refines those with geospatial information on relative ecosystem service provision and natural hazard risks. As for the latter, we argue that the dependency on ecosystem services can also be understood and serve as a nexus for a company’s vulnerability to corresponding natural hazards. For instance, the dependency of agriculture on soil retention (ecosystem service) might make it susceptible to soil erosion risk; similar relations 2see https://environment.ec.europa.eu/strategy/biodiversity-strategy-2030_en. 3see European Commission, accessed on December 2023, Water scarcity and droughts: Preventing and mitigating water scarcity and droughts in the EU. 4see https://ec.europa.eu/newsroom/env/items/803760/. 2 hold for flood and drought risk. Combining this data provides a more precise formulation of nature-related physical risks. This helps to unveil the actual share of European SMEs long-term debt, which we use as a proxy for loans held by European banks, that might be exposed to those risks and be a source of possible financial instability. The rest of this study is structured as follows. Section 2describes in more technical terms how ecosystems relate to economic activities and why this is important for financial risk assessment. Section 3describes the data used. Section 4displays European SMEs’ exposures to ecosystems and natural hazards. Section 5concludes. 2 Economic dependency on ecosystem services The starting point for our nature-related financial risk (NRFR) analysis is the Encore framework as described in Natural Capital Finance Alliance (2022). While many different approaches for ecosystem and biodiversity assessments exist, the financial community has widely accepted the NRFR framework (for instance, see Calice et al.,2021;Carvalho et al., 2022;Boldrini et al.,2023) as it comprehensively and transparently provides materiality ratings for various ecosystem service dependencies and impacts for the different economic sectors. For instance, it provides a dependency on groundwater for a specific industry subsector, and hence also a company that operates in this subsector. While companies are dependent on ecosystem services, they can also harm ecosystems. This so-called double-materiality relationship is known from climate risk assessments. Dependencies reflect the fact that the economy or a firm benefits from using ecosystem services as inputs and is subject to vulnerabilities stemming from a disruption of those (nature physical risks). At the same time, economic activities adversely impact ecosystem services via various modes of pollution, making certain types of production susceptible to prohibitive legislation (nature transition risks). This study focuses solely on ecosystem dependency and climate (physical) risks (see Figure 1). European data on the former is provided by the European Commission’s Joint Research Centre (JRC) Integrated Assessment of Ecosystem Services (INCA) project in the form of ecosystem accounts, and the JRC Risk Data Hub (RDH) provides natural 3 hazard data for Europe.5A sector or firm that is highly dependent can suffer higher costs or even production failure in the case of an ecosystem services interruption. For this reason, we inform the share of highly exposed firms with geospatial data on exposures concerning local ecosystem provisioning shortage and natural hazards. In addition, we complement natural hazard metrics, which are complementary and studied in the context of physical climate risks. An ecosystem dependency (physical risk) block, as proposed in this paper, and an ecosystem impact (transition risk) building block would be necessary to run a comprehensive nature-related stress test. Table 1lists all ecosystem dependencies Figure 1 Firm dependency on ecosystem services Company A Nature-related risk exposures (Encore) Sector Natural Capital Accounting Ecosystem services (JRC INCA) Soil retention Flood protection Water provision Geospatial Natural hazards (JRC Risk Data Hub) Soil erosion Flood risk Drought Geospatial Physical risk Dependencies Impacts Nature risk Climate risk Source: Hirschbuehl (2024). . incorporated by Encore with a grouping and highlights the subset of services evaluated in this study. Ecosystem services can be grouped according to their functionality into four categories: material services, e.g. serving as direct physical inputs to production such as 5see https://ecosystem-accounts.jrc.ec.europa.eu/ and https://drmkc.jrc.ec.europa.eu/ris k-data-hub/. 4 employees. There are about 5.7 million micro firms in our sample. While more numerous, their economic weight remains below that of small and medium-sized companies. Table 3 Summary statistics (mean) by firm size category Micro Small Medium Long term debt (EUR) 129000 1614134 7128637 Total assets (EUR) 564241 8028849 40092799 EBITDA (EUR) 31619 461856 2100109 Number of employees 5 30 123 Observations 5732128 734262 171003 Source: JRC elaboration. . 3.1 Encore sectoral risk exposures to ecosystem services Encore is a holistic framework that links ecosystem services and economic activities. In this version of the mapping, economic activities are provided in the GICS11 classification, which is converted into 4-digit NACE(rev.2).12 This allows the linking of ecosystem service dependency risk exposures with firms in ORBIS. The EU energy mix is used to calculate a weighted average of dependency exposures for the electricity sector. Risk exposures are provided as a materiality rating (see Table 4). No direct dependency and very low dependency ratings are aggregated as the separation is, in our analysis, not economically meaningful. High and very high materiality ratings display a firm’s high susceptibility, incl. production failure, to an interruption of an ecosystem service. However, high materiality ratings can also indicate vulnerabilities to corresponding natural hazards. Figure 4displays an overview of the Encore ecosystem dependency exposures of longterm debt in the sample for the relevant ecosystem services used in this paper, which are flood protection, erosion control and three categories of water (surface, ground, and an additional metric that uses the maximum materiality of each). The ecosystem dependency is purely determined based on the sector of a firm and does not contain geospatial information 11Global Industry Classification Standard. 12European statistical classification of economic activities. 11 Table 4 Materiality ratings for ecosystem services Materiality Impact on the production process Rating Very High (5) The ecosystem service is critical and irreplaceable in the (VH) production process. High (4) Production process is extremely vulnerable to the disruption (H) of the ecosystem service. Medium (3) Production process can take place without the (M) ecosystem service due to availability of substitutes. Low (2) Most of the time, the production process can take place (L) even with full disruption of the ecosystem service. Very Low (1) Production process can take place even with full disruption (VL) of the ecosystem service. No link (0) Production process is independent of the ecosystem service. Source: Natural Capital Finance Alliance (2022). on whether the ecosystem service is stressed in a region. This descriptive analysis suggests that about 10.1% of European firms’ long-term debt depends highly (H) or very highly (VH) on the ecosystem service flood protection. Similarly, 67.2% of agricultural companies’ long-term debt is high or very highly exposed to the ecosystem service erosion control, while in the rest of the economy, 27.9% of the portfolio is critically exposed to surface water and 7.5% to groundwater. The subsequent analysis will in parts also provide ecosystem dependency exposures by firm size category or other variables, but also a refined insight of highly reliant companies using geospatial information. 3.2 Ecosystem services The ecosystem service data (Table 2) utilized has been sourced from the INCA project (see La Notte et al.,2021). This data follows Ecosystem Accounting (EA), which is based on the global standard System of Environmental Economic Accounting (SEEA) and tracks the state of ecosystems. Ecosystems are complex, and they are often calculated using proxies that best represent the ecological process. Further, when no direct data is available, biophysical models are used to estimate the proxy for the process. Some of these models also take specific natural hazard metrics as observable input. While not reflecting the same mechanism, one needs to be aware of possible endogeneity when combining this data. The value of ecosystem services, measured in physical and monetary terms, estimates what an 12 Figure 4 Long-term debt risk exposure to various ecosystem service dependencies (erosion control for agriculture solely, NACE<400), 2020. 59.2 30.8 6.7 3.4 Flood protection 11.2 21.6 1.3 65.9 Erosion control 55.2 2.6 14.4 23.8 4.1 Surface water 54.2 2.6 35.7 2.8 4.7 Ground water 54.1 2.6 15.4 22.8 5.1 max (surf., ground.) VH H M L VL Source: JRC elaboration. ecosystem can provide yearly. In the subsequent analysis, the data is processed at the NUTS3 level. Data for ecosystem services accounts is produced under the INCA project, which has provided data for four accounting periods: 2000, 2006, 2012, and 2018 (see Vysna et al.,2021). We rely on the 2018 observation in the subsequent analysis. The approach employed for modelling soil retention and flood protection services involves assessing the interplay between two key components: ecosystem service potential and ecosystem service demand (see La Notte et al.,2019). Ecosystem service potential represents what ecosystems can provide, irrespective of whether it is utilized. In contrast, ecosystem demand refers to the total demand by the economy and society, regardless of whether it is fulfilled or unmet. The spatial interaction between potential and demand determines the actual flow, which identifies what is eventually utilized as ecosystem service flow by the economy and society. A mismatch can occur either because the potential supply exceeds the demand or because of an economically relevant shortage when demand exceeds supply, resulting in unmet demand. The unmet demand becomes particularly relevant when examining vulnerability to hazard risks. Table 5reports a taxonomy of definitions. 13 Table 5 Ecosystem service components in ecosystem accounting. Ecosystem Service Component Definition Units of measurement Flood control Demand The extent of economic assets located in floodplains that can be delineated using flood hazard maps Ha Unmet demand The extent of economic assets located in floodplains that are not covered by the service potential Ha Soil retention Demand Soil loss per hectare by ecosystems when ecosystem protection is not provided Tonnes/ha yr −1 Unmet demand Net soil losses Tonnes/ha yr −1 Source: JRC elaboration. . We calculate an indicator for local ecosystem service provisioning shortage (EPS) for each ecosystem service as Ecosystem Provisioning Shortage = Demand −Unmet Demand Demand −1 .(1) which results in a metric indicating insufficiency of ecosystem provision if larger than 1. Negative values are discarded as unmet demand cannot exceed demand, indicating that those values might result from measurement errors potentially due to geographically complex structures. We assign materiality ratings for ecosystem underprovisioning based on the thresholds outlined in Equation 2and geospatially illustrated in Figure 6. Ecosystem Provisioning Shortage =                                V L if EP S ≤1.025, L if 1.025 < EP S ≤1.05, M if 1.05 < EP S ≤1.15, H if 1.15 < EP S ≤1.25, V H if 1.25 < EP S. (2) In the first part of the analysis, this study investigates key variables, e.g. long-term debt, of companies and their exposure to a particular ecosystem service of interest. This is achieved by utilising Encore sectoral risk exposures. The share of companies’ long-term 14 debt that has a high (H) to very high (VH) exposure is susceptible to ecosystem service interruption as by definition it implies production failure. This share is then decomposed using geospatial information on the specific ecosystem or natural hazard risks (see Figure 5). Figure 5 Illustration of exposure versus risk VH H M L VL H M L VL VH ENCORE dependency exposure H-VH ENCORE dependency exposure and ecosystem shortage or natural hazard Source: JRC elaboration. 3.2.1 Flood control In the case of flood control, both potential and demand are established using a spatially explicit model developed by the European Commission’s JRC for the INCA project, specifically through the accounting application of ESTIMAP (see Vallecillo et al.,2019).13 The evaluation of ecosystem supply involves five primary steps: 1) scoring land cover classes using the curve number; 2) adjusting the curve number based on imperviousness; 3) modifying the curve number score according to slope; 4) incorporating natural and semi-natural land cover in riparian zones; and 5) mapping the service providing area (detailed explanation in Vallecillo et al.,2019). The demand for flood control is determined by the expanse of economic assets in floodplains. Floodplains were determined based on those outlined in the flood hazard maps at the EU level for the maximum available return period, which is 500 13Table 5delineates the components of ecosystem accounting for each service, along with their corresponding units of measurement. 15 years.14 Flood control as an ecosystem service involves the regulation of water flow by ecosystems to mitigate or prevent potential damage to economic assets (such as infrastructure and agriculture) and human lives (see Haines-Young and Potschin,2018). Various ecosystems, particularly forests, shrublands, grasslands, and wetlands, can reduce runoff by retaining water in the soil and aquifers and slowing the water flow. This action helps prevent the rapid downstream runoff of surface water, resulting in a decrease in peak runoff and, consequently, mitigating the adverse impacts of flooding on farmland, buildings, and infrastructure. The derived measure of ecosystem provisioning shortage for flood retention is displayed in the left panel of Figure 6. Countries that are also experiencing water scarcity, for instance, Spain and Italy, but also water-richer countries, such as Sweden and Finland, have a high unmet demand. Figure 6 Ecosystem provisioning shortage, (left) flood protection and (right) soil retention. . VH H M L VL No Value . VH H M L VL No Value Source: JRC elaboration. . 14This map is accessible in the JRC Data Catalogue: Flood Hazard Map for Europe, 500-year return period. 16 3.2.2 Soil retention For soil retention, ecosystem supply is determined through the vegetation cover factor, which incorporates physiological and ecological characteristics of vegetation (see Panagos et al.,2015). These include factors like vertical and horizontal canopy structure, root systems, and specific functional traits of plants, all within specific abiotic conditions. The potential for soil retention is determined by the Vegetation Cover Factor (C-factor), which is calculated in relation to the maximum C-factor and rescaled to a range between 0 and 1 (see La Notte et al.,2021). Consequently, lower C-factor values correspond to increased soil retention within the ecosystem. Augmenting vegetation cover, adopting protective crops, and deploying soil conservation measures have the potential to elevate soil retention within ecosystems. The determination of C-factor estimates for arable and non-arable land necessitates distinct approaches and data sources, as outlined by Panagos et al. (2015). Ecosystem demand represents the societal requirement for soil retention. It is estimated based on the counterfactual model applied in the Revised Universal Soil Loss Equation (RUSLE) (see Panagos et al.,2015), and it is calculated as the total soil loss (tonnes ha per year). The absence of ecosystem protection represents the worst-case scenario with the least potential for ecosystems to retain soil. Areas with higher risks of erosion present higher demands for the protective role of ecosystems. In INCA the focus is on the contribution of cropland to the agricultural economic sector. By applying a constant C-factor of 0.55 for the whole EU in the RUSLE equation, it is possible to quantify and map the amount of soil that could potentially be lost due to water erosion under the lowest ecosystem supply. On-site soil retention is a vital ecosystem service that profoundly impacts soil quality and agricultural productivity. Soil retention is provided by almost all terrestrial ecosystem types, but only when provided on cropland it is accounted as ecosystem service (see La Notte et al.,2022). Defined as the ability of ecosystems to mitigate on-site erosion rates resulting from rainfall (see Haines-Young and Potschin,2018), this service plays a crucial role in maintaining soil health. If left unchecked, erosion can lead to the loss of topsoil, adversely affecting cropland productivity and triggering a detrimental cycle of further degradation. The significance of on-site soil retention is manifold. Ecologically, it sustains optimal soil 17 conditions by preventing erosion, thereby preserving the fertility and characteristics of soils. Economically, it is indispensable for agricultural production, as the retained soil provides and preserves nutrients, diminishing the need for additional inputs like fertilizers. This not only benefits the environment by minimizing the use of potentially harmful chemicals but also carries economic implications by reducing production costs for farmers. The South of Spain, Italy, and Eastern Romania experience comparatively a high unmet demand for this ecosystem service (see Figure 6, right panel). 3.2.3 Water We use the WEI+ to measure unsustainable water use and hence provisioning. The metric already displays a provisioning at-risk perspective. We follow De Roo et al. (2021) in calculating the WEI+ indicator, which illustrates the pressure on renewable freshwater resources due to water demand. The authors show that in many regions, annual renewable freshwater use is unsustainable across Europe. Notably, 29% of the EU-27 territory, excluding Italy, was affected by water scarcity in 2019, while total water abstraction has been declining by 15% between 2000 and 2019. The authors find water scarcity more common in southern Europe, with approximately 30% of the population living in areas with permanent water stress and up to 70% experiencing seasonal water stress during the summer. However, water scarcity is not limited to the southern part of Europe. It extends to Western Europe, where water scarcity is caused by high urban population density, joined with high levels of abstraction for energy and industry. For our purposes, we calculate the index at the NUTS3 instead of the sub-river-basin district level, as usually done. Otherwise, we calculate the water exploitation index similar as in the literature: W EI+ = net consumption local availability + upstream inflow (3) In this context, water availability reflects the local precipitation minus the evapotranspiration plus river inflow coming from upstream. Net consumption is all water abstractions minus return flows, meaning water lost from the water cycle. Hence, water consumption excludes power plant cooling and drinking water, which return largely to the water cycle. 18 A WEI+ with values above 20%, indicates water scarcity, while values above 40% indicate severe scarcity and that the freshwater use is likely unsustainable. We calculate a seasonal metric, investigating whether water scarcity exists for at least two months a year and annually, with the latter being usually less sensitive. Then, we take the maximum value for each region between 2015 and 2021. Materiality ratings are assigned according to the thresholds outlined in Equation 4. Water stress =                V L if W EI+≤0.2, H if 0.2< W EI+≤0.4, V H if 0.4< W EI +. (4) For regions that suffer severe water scarcity, using freshwater resources is likely unsustainable, potentially going along with or resulting in groundwater depletion. To investigate this, we employ a measure of groundwater depletion as described in De Roo et al. (2021) and Gelati et al. (2020). So far, a statistically significant decline in the trend of groundwater storage is mainly observed in the South of Europe, such as Southern Spain, Greece, Sicily, Bulgaria and South-Eastern France, but also in the South of Germany and Switzerland. As we are interested in current developments and as more efficient water use might be implemented, we use this measure’s mean between 2019 and 2021, acknowledging the limitations of the proposed metric. Any unsustainable amount used is assigned a materiality rating VH. To be fully aligned for sustainability assessments, the unsustainable use would have to be reported as a share of groundwater total. The obtained measures for these periods are illustrated in Figure 7. Particularly, Spain, Sardinia and Southern Italy experience seasonal water scarcity as measured by the WEI+, with unsustainable groundwater use primarily reflecting this water stress. 3.3 Natural hazards Further, we use the natural hazard data (Table 2) hosted on the JRC Risk Data Hub, a web-based platform that contains harmonized risk data and methodologies for disaster risk assessment in Europe (see Antofie et al.,2019). The RDH is set to become the reference 19 Figure 7 Ecosystem provisioning shortage, (left) WEI+ seasonal and (right) unsustainable groundwater use. . VH H M L VL No Value . VH H M L VL No Value Source: JRC elaboration. . platform for standardised recording and collection of comprehensive and granular climaterelated losses and physical climate risk data at the EU level in the context of the new EU Strategy on adaptation to climate change. We use the absolute measure of flood risk for commercial buildings for a 25-year return period, estimated mean soil erosion risk from 2016, and the SPI 3-month mean value between 2016 and 2022 to capture drought risk. It is important to mention that the described natural hazard data may partially serve as input for calculating the ecosystem services described above. 3.3.1 Flood risk The flood risk indicator measures the potential impact of a hazard for a specific area or community in a given period of time. It compounds two different components associated with the occurrence of a natural hazard, measuring respectively the exposure and the vulnerability to the specific hazard. The exposure component is calculated from geo-localised information on relevant flood metrics, such as frequencies and intensities, with layers for 20 dependencies provided by surface and groundwater dependencies. The mid panel illustrates the exposure of alternative firm key variables to water dependency. Interestingly, about 10% of profits and employment appear to be very highly dependent on water, while only half of the long-term debt might be exposed. The right panel shows a similar distribution of water dependencies by firm size, with between 25 to 30% of long-term debt being at least highly exposed to water dependencies. Figure 12 (left) Encore different water dependency exposures of long-term debt, (mid) maximum water exposure measure of firm key variable and (right) maximum water exposure measure by firm size. 55.2 2.6 14.4 23.8 4.1 Surface water 54.2 2.6 35.7 2.8 4.7 Groundwater 54.1 2.6 15.4 22.8 5.1 max(surf, ground) LT debt VH H M L VL 63.6 1.6 15.0 14.5 5.4 Total assets 52.4 2.4 23.1 11.8 10.3 EBITDA 56.5 1.7 27.7 4.9 9.2 Employment max (surf, ground) VH H M L VL 53.9 0.4 18.4 22.3 5.0 Micro 54.7 5.4 14.9 19.9 5.1 Small 53.7 0.9 14.6 25.7 5.1 Medium LT Debt, max (surf, ground) VH H M L VL Source: JRC elaboration. . The left and the right panel of Figure 13 display the shares of surface and groundwater H and VH-exposed long-term debt (see Figure 12) that are exposed to seasonal water scarcity as measured by a 6-month WEI+, a measure of annual drought, and groundwater unsustainable use - all indicating distortions to the water cycle. Comparatively little, solely 9% of 27.9% of all long-term debt exposed to surface water dependencies (2.51% of total long-term debt) occasionally suffer seasonal water scarcity. In contrast, 48.1% of this debt share is also exposed to drought conditions, while only 2.6% of this debt is located in areas with unsustainable groundwater use. In contrast, high groundwater-dependant (H-VH) long-term debt has high exposures to seasonal water scarcity (19%) and drought conditions (37.1%). At the same time, 19.1% of highly groundwater risk-exposed debt (7.5% of all longterm debt) operates in areas already experiencing unsustainable groundwater use. Despite a lower share of companies appearing to be exposed to groundwater dependencies, 2.6% of European SME total long-term debt in the sample might suffer from groundwater shortages 27 in the long run. Figure 13 Long-term debt exposure to WEI+ seasonal, annual drought and unsustainable groundwater as a share of long-term debt exposed to H-VH (left) surface water and (right) groundwater. 91.0 4.4 4.6 WEI+ seasonal 51.9 40.5 7.6 Drought annual 97.4 2.6 Groundwater unsust. use surface water H-VH LT Debt 81.0 3.7 15.3 WEI+ seasonal 62.9 31.4 5.7 Drought annual 80.9 19.1 Groundwater unsust. use groundwater H-VH LT Debt VH H VL Source: JRC elaboration. . 5 Conclusions This article investigates nature-related risk exposures of European SMEs’ performance variables, and connects long-term debt, with regional measurements of ecosystems and climate risks to gauge possible implications for financial stability. The analysis reveals moderate direct risks under current conditions in the EU aggregate long-term debt portfolio. Possible ecosystem degradation or potentially intensified natural hazards due to changing future climatic conditions may increase the risks in the coming decade, which, however, goes beyond the scope of the current analysis. Both ecosystem provisioning shortages and natural hazards tend to be regionally concentrated, potentially adversely affecting companies’ operations and locally operating banks in some regions. At the same time, the current results constitute a first assessment based on approximations that call for further refinement and require careful interpretation. In particular, more work appears needed to achieve the complete suitability of current variables for sustainability assessments as required in the context of economic or financial analysis. The regional concentration of the existing - potentially not yet perfect - measures, if not interpreted cautiously, may imply the risk of economically weakening periphery regions, where 28 many economic structures might already operate sustainably from a nature-risk point of view. Further, the analysis could be extended to include more ecosystem services, such as soil quality or water purification. It may be interesting to extend the analysis to non-EU supply chain considerations to complete the picture of possible vulnerabilities. Finally, reliable short-term scenarios on natural hazards and ecosystem services could aid in refining risk analysis and developing models to investigate whether these risks have the potential to intensify in the near term. References Ahopelto, L., N. Veijalainen, J. H. Guillaume, M. Keskinen, M. Marttunen, and O. Varis (2019). Can there be water scarcity with abundance of water? Analyzing water stress during a severe drought in Finland. 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