Ecosystem Services as a Framework for Transformation of the Rhenish Mining Area

Abstract

This book chapter discusses the concept of ecosystem services as a potential framework for socio-ecological transformation processes in mining areas toward resilient and sustainable post-mining landscapes. As mining landscapes all around the world are undergoing enormous transformation processes, finding the best balance between economic interests, social implications, and ecological and climate services is of utmost importance. Those mining landscapes provide indispensable regulating, provisioning, and cultural services while preserving or fostering stable ecosystems with high and regional typical biodiversity. Despite their crucial contributions to human well-being, the services in these landscapes are only rarely considered in spatial and landscape planning decisions. With accelerated global changes, those ecosystem services, however, become increasingly important. Thus, the authors propose the concept of ecosystem services and inclusion of biodiversity and discuss mechanisms of qualitative and quantitative evaluation, budgeting, and pathways for decision making. For this purpose, a first basic qualitative assessment of ecosystem service potentials for the transformation of the landscape of the Rhenish Mining Area was performed exemplarily.

1 Introduction: The Role of Ecosystem Services in (Post-Mining) Landscapes

In almost all areas of the world, landscapes are under constant transformation. Land-use changes from natural or semi-natural to anthropogenically utilized areas, e.g., for agricultural purposes or by expanding urban and suburban areas, are almost ubiquitous and pose enormous challenges for nature and society. In particular, ecosystems, their functions, and biodiversity in general are threatened and under pressure. Open-cast mining certainly has one of the strongest impacts on ecosystems, habitats, geomorphology, soil formation, water balance, and cultural landscapes (Gerwin et al. 2023). This leads to long-term changes in the socio-ecological and socio-economic structure of a region (Zerbe 2019). However, post-mining areas can provide versatile, valuable biotope mosaics (Kirmer and Tischew 2019), and high-potential cultural landscapes (Zerbe 2019). One of the major challenges is, thus, the transformation of the open-cast post-mining landscapes by re-cultivation and re-naturalization into sustainable landscapes well-functioning for human and nature purposes in the long term.

An important framework for transformation of landscapes can be the utilization of the concept of ecosystem services (ES) in order to identify potentials and deficits of landscapes. ES constitute an important approach to assess and valuate the goods and services of nature for human purposes.¹ The assessment quantifies ES in biophysical, monetary, social, or mixed terms to consider the importance of ES supply and demand in policy, economic, or spatial-planning decision making. It can promote the development of sustainable socio-ecological and economic landscapes and in case of this book chapter in particular post-mining landscapes in transformation. Therefore, a spatial explicit and accurate examination of numerous, complex, and interlinked ES, strongly influenced by varying ecosystem functions, biodiversity, and human demands, is necessary. ES have gained a recognized but widely discussed status in international multidisciplinary research. In addition, the concept is extended to policy, economics, and spatial planning (e.g., von Haaren et al. 2016). Although the concept is sometimes discussed controversially (e.g., Gowdy et al. 2010), it offers an enormous potential for assessment of landscapes in transformation.

This book chapter addresses the following three questions: (i) How can ES and biodiversity be qualitatively and quantitatively assessed in landscapes?, (ii) What conclusions can be drawn about the potential of ES in the Rhenish mining area?, and iii) Can the ES assessment contribute to a transformative change? The chapter starts with a basic overview of the state of the art of the concept of ES and introduces the different methods of ES assessment and valuation. This general background is exemplarily applied as a framework to assess the current situation in the Rhenish mining area, Germany, as a current example of a mining region undergoing large transformational processes. Here, a look at ES potentials provides insights into different aspects of ES spatial distribution and their characteristics in the Rhenish mining area. After assessment of the status quo, mechanisms of evaluation, budgeting, and pathways for decision making are elaborated as potential tools for sustainable transformative processes in mining areas. Finally, future perspectives elucidating the transformational impact for the region and a vision for a sustainable post-mining landscape development are provided.

2 State of the Art of Ecosystem Service Assessment and Valuation

This section first provides a general overview about the state of the art of ES research and the concept of ES, before highlighting different methods of ES assessment and valuation such as biophysical, economic, and socio-cultural approaches including modeling and mapping of ES.

2.1 The Concept of Ecosystem Services

ES can be defined as “the direct and indirect contributions of ecosystems to human well-being” (de Groot et al. 2010: 25). This constitutes a further development of the definition used in the Millennium Ecosystem Assessment (MEA) which defines ES as “the benefits people obtain from ecosystems” (MEA 2005a: V) specifying the benefit factor in its relation to an anthropogenic purpose.

In general, the ES concept aims at two interrelated intentions (c.f., Potschin and Haines-Young 2011): (a) to increase awareness of the contributions of ecosystems to human life, and (b) to measure the interrelation of ES potential, supply, flow, and demand for science and decision making. ES can provide crucial approaches to the current landscape potentials and demands that have to be met for a sustainable transformation, in particular in the framework for transformation of mining regions.

While the concept itself is commonly accepted, most frameworks are disputed. Due to the high complexity and variance of socio-ecological systems, they are challenging to understand and model (Potschin and Haines-Young 2011). Ecosystems offer the potential for multiple ES and are affected by other ecosystems as well as human contributions. Holistic approaches are necessary, but so far not comprehensively implementable (Kumar et al. 2010). The supply potential, actual flow, valuation, and demand of ES depend on the respective perspectives as well as local and temporal conditions (MEA 2005a).

2.1.1 Trends in ES Research

Since the 1970s, the benefits of nature for humans through ecological, economic, and social-cultural values, have been studied in increasing detail. In ecological-economic theory, environmental resources have started to be considered again as natural capital in business decision making (de Groot et al. 2017). Since the 1990s, interest in ES increased both in science and practice. Major milestones were the publications of Costanza et al. (1997), Daily (1997), and the MEA (2005a), which investigated the state and change of ES on different scales, assessed future scenarios as well as proposed policies. It had placed ES on political agendas. The Economics of Ecosystems and Biodiversity (TEEB) study (2010) was conducted due to the increased political awareness of the economic significance of the global loss of biological diversity. The objectives of TEEB were to develop stakeholder-oriented methods for economic accounting and valuation of ES. Most of today's frameworks expand on the results of both (e.g., Maes et al. 2013; Haines-Young and Potschin 2018; Newcomer-Johnson et al. 2020). In Fig. 1, the MEA framework of interactions between biodiversity, ES, human well-being, and drivers is conceptualized.

Fig. 1

Millennium Ecosystem Assessment conceptual framework of interactions between biodiversity, ecosystem services, human well-being, and drivers of change. Remark: Today, supporting services are mostly referred to as ecosystem functions, in respect to their intermediate character rather than final output (own representation of the original figure; MEA 2005a)

In their review, Potschin and Haines-Young (2011) emphasized the importance of a spatial perspective to offer advantages to characterize the socio-ecological components of ES and to understand their dynamics. For the past decade, ES research has focused particularly on classification, modeling, mapping, and the relationship to ecosystem conditions.

ES research in the European Union (EU) has been strengthened by the adoption of ES in the Biodiversity Strategy 2020 (European Commission 2011) in response to the Aichi Biodiversity Targets of the International Convention on Biological Diversity (CBD) in 2010. In addition, the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) was established in 2012 (c.f., de Groot et al. 2017). As part of the EU targets, the mapping, assessment, and economic accounting of ES were requested from the member states (European Commission 2011). The implementation was overseen by the working group Mapping and Assessment of Ecosystems and their Services (MAES) and scientifically enhanced by several research projects. The new EU Biodiversity Strategy 2030—as part of the European Green Deal—focuses on the restoration of ecosystems for a sustainable provision of ES (Maes et al. 2020). The concept of ES can also be linked to the idea of Sustainable Development Goals (SDG) on different scales (Yang et al. 2020).

Alongside the EU's framework, other national assessments of ES have been carried out such as the UK National Ecosystem Assessment 2011 and NESCS-Plus (Newcomer-Johnson et al. 2020) and, for example, research on the methodology for measuring and valuing ES has been conducted in China since the mid-1990s (c.f., Liang et al. 2020).

Another trend in ES research is the view of people and nature instead of nature for people (Mace 2016). Shaping ES research into a post-normal science requires a process of embedding the knowledge gained in wider societal discourses in each subsequent research step. An important difference in a people and nature approach is that actions should not be for nature, but by nature. Thus, the recognition of the indispensability of environment and humans and the implementation of nature-based solutions for socio-economic problems from various perspectives should be the target of actions (Potschin et al. 2016).

To achieve such a change, a more uniform concept is necessary. Comprehensive discussions were conducted about how to define, classify, and valuate ES (e.g., Mace et al. 2011; Boyd and Banzhaf 2007; Potschin and Haines-Young 2011). A standardized definition of ES is yet to be determined, e.g., regarding the question of the intrinsic value of nature. In this case, the ethical question arises whether nature should really serve humans, which is implied by the nomenclature. Furthermore, the discourse deals with the distinction of functions and services and into which sections ES should be divided. To what extent ES can be characterized as end products or intermediate services has depended so far on the differentiation and interpretation of individual scientists. This is crucial to whether ES are categorized in provisioning, regulating, and cultural services (e.g., Potschin and Haines-Young 2011; Maes et al. 2013) or additionally in intermediate (Fisher et al. 2009), habitat (de Groot et al. 2010), or supporting services (MEA 2005a). The most common classification catalogs are those proposed by the MEA (2005a), TEEB (2010), UK National Ecosystem Assessment (Mace et al. 2011), and the Common International Classification of Ecosystem Services (CICES) (Haines-Young and Potschin 2018). The individual catalogs offer different designations and subdivisions of the ES.

2.1.2 Comprehension of Fundamental Concept(s) and Classification of ES

One common ES concept model is the cascade model by Potschin and Haines-Young (2011) describing the socio-ecological system as a pathway. The pathway links the processes from environmental structure to values of human well-being (Fig. 2). ES are considered as the interface between humans and nature. The model represents an attempt to contextualize inter- and transdisciplinary aspects that must be included in an ES analysis. The understanding as a cascade rather than a step-by-step model emphasized the issue of setting universal boundaries between the labeled stages. Thus, the model is consistent with the description of ES according to Costanza (2016: 18), where ES are “therefore not the product of a linear chain from production (means) to direct benefits for people (ends) with no feedbacks or any of the other complexities of the real world.” All ES are, by definition, means to the end of human well-being. In addition, the model offers the opportunity to gain an understanding of the inconsistency in the definitions and ES appreciations. For example, the relationship between the definition of ES as benefit used in the MEA and the terminology of direct and indirect contributions to human well-being in TEEB becomes apparent. Likewise, the cascade model provides a way to separate intermediate and supporting from final services, e.g., to avoid double counting. It considers that the system is too complex for an exclusive separation. However, the model has difficulties such as the treatment of the term function. While, here, it can be understood as the capacity of an ecosystem to provide a potential service (after de Groot et al. 2002), the term can have other ecological connotations. Examples of those are any ecosystem processes or the tasks of ecosystems for human benefit (Jax 2016).

Fig. 2

Cascade model (own representation of the original figure; Potschin and Haines-Young 2011, 2016a)

Sustainable management of ES can only be achieved through a supply–demand balance. Therefore, a spatial explicit assessment of ES potential, supply, flow, and demand is necessary (Syrbe et al. 2017). After Syrbe et al. (2017) ES potential is based on the ecosystem properties and condition describing the potential of sustainable provision of an ES; the ES supply is the amount of a service provided by an ecosystem considering the human input within a certain time period, irrespective of actual use. Delimited to the supply, the ES flow is “the amount of ES that are actually mobilized in a specific area and time” driven by the demand (Syrbe et al. 2017: 153). The demand for ES corresponds to the needs by society, stakeholder groups, or individuals. Furthermore, it depends on cultural and individual factors as well as ES availability.

The service providing unit (SPU)/service benefiting area (SBA) approach differs in spatial units that are the source of an ES (supply) and areas that realize benefits from an ES (demand). The spatial relationship between SPUs and SBAs can be in situ, omnidirectional, directional, or decoupled (Syrbe and Walz 2012).

For the assessment, monitoring, and management, an ES classification is needed that can be situation-based and spatiotemporally quantified. CICES is recommended in the EU, whereby the holistic approach as well as the flexible and hierarchical structure were emphasized as its advantages (Maes et al. 2013). It is based on the Systems of Environmental Economic Accounting (SEEA) of the United Nations Statistical Division (UNSD) and the basic terminology from the MEA. Since 2018, a revised version (version 5.1) has been available (c.f., Haines-Young and Potschin 2018). CICES builds on the cascade model. For every ES, ecosystem attributes or behaviors as well as the benefitting purposes are defined. In CICES, classified services should be seen as potential final services which can have either final or intermediate characteristics in different situations (Haines-Young and Potschin 2018).

The question of including abiotic outputs that contribute to human well-being is relevant. In line with the MEA, TEEB, and the IPBES, ES refer to living (biotic) systems. However, some scientists and decision makers include abiotic components of natural capital. Examples can be the engagements of fields to produce wind power or the extraction of fossil fuels (c.f., MEA 2005b; Burkhard et al. 2012; Müller et al. 2020). In CICES, the focus lies on biotic systems. Nevertheless, version 5.1 includes the option to integrate abiotic processes through the holistic approach classifying geophysical processes in ES and abiotic outputs. Additionally, this offers the advantage to deal with services that cannot be distinguished into biotic or abiotic processes easily. An example is the integration of water for drinking purposes which is uniformly classified as ES in standard works. In CICES version 5.1, surface and groundwater used for nutrition, materials, or energy are classified as abiotic outputs to allow a correct allocation (Haines-Young and Potschin 2018).

CICES is organized into five hierarchical levels. The top level comprises the sections based on the MEA: provisioning services, regulation and maintenance services, and cultural services. However, supporting services are not included as they underpin the output of final services and are not regarded as separate services but rather as facilitating processes for the other categories (Haines-Young and Potschin 2018). Provisioning services are all nutritional, material, and energy services (including abiotic services such as water used for nutrition, materials, or energy). Regulating services include the moderation of the environment by living organisms in a way that contributes to human well-being. The category of cultural services considers all non-material and non-consumptive services of ecosystems that affect the human mental and physical state. The structure of CICES allows cross-referencing to other classifications for international and temporal comparability (Haines-Young and Potschin 2018).

2.2 Assessment and Valuation of Ecosystem Services

The following section addresses the theoretical background of ES assessments. Most ES assessments are either habitat-based, process-based, or place-based. Habitat-based approaches investigate ES based on the stock, status, or change of biodiversity at landscape levels. Advantages are, e.g., that the method can often work with existing data and can be applied well to conservation issues. Disadvantages can be the ambiguity of relationships between different habitats and their weighting. Process-based approaches start with the structural and functional relationships affecting ES. Such methods especially benefit for a reliable assessment, if modeling alternative assumptions or scenarios is aspired. However, usually, the methods are too complex to accurately represent multifunctionalities. The place-based approach addresses ES as a bundle in a cross-cutting and time-sensitive manner, focusing on socio-ecological systems. This method can be time-/cost-intensive and requires transdisciplinary collaboration but contributes to a specific local comprehension (Potschin and Haines-Young 2016b).

Overall, ES frameworks are similar in their assessment proceeding: ES are measured with selected quantitative and/or qualitative indicators which are afterward contextualized by a valuation system (e.g., MEA 2005a, Maes et al. 2020). Assessments should include the underlying reasons for the inquiry as well as the time-sensitive parameters and delimitations of the study area (Syrbe et al. 2017).

2.2.1 Valuation of Ecosystem Services

Different valuation approaches are theoretically discussed and applied in scientific literature. It is challenging to measure ES value (changes)—especially in comparison. Besides the difficulties of accurate quantification, the question for whom and when a value is generated has to be considered. Values can be plural, context-dependent as well as not-static (Dunford et al. 2017). Valuation is always linked to conscious or unconscious human decisions about ecological systems and their changes. Some say that finding a common value is almost impossible, especially for intangibles such as human life or long-term ecological benefits (Costanza 2016). However, in everyday life, a valuation of ES is usually made. Gómez-Baggethun et al. (2016: 103) merged previous definitions that ES “valuation can be defined as the act of assessing, appraising, or measuring value, primarily in terms of worth, meaning, and importance, but also in relation to principles and moral duties toward biodiversity.” A division into economic, ecological, and socio-cultural values is widespread in literature (c.f., Potschin and Haines-Young 2011; Costanza 2016; Gómez-Baggethun et al. 2016).

On one hand, economic valuation is the most controversial-debated approach, but on the other hand yet commonly applied (Gómez-Baggethun et al. 2016). It is based on a transfer of supply and demand changes of ES into neoclassic economy theory (Brander and Crossman 2017). An economic valuation, however, cannot stand without a reliable and suitable ecological assessment, a quantitative assessment of ecological indicators is a prerequisite for applying economic valuation methods (Kumar et al. 2010). A common form of economic valuation is the calculation of a total economic value. It quantifies how supply and demand behave under marginal ecosystem change (Potschin and Haines-Young 2011). The main problem here is that market data usually do not exist for ES—due to the public good character of most of these services. Therefore, economic values have to be derived directly or indirectly from other data—by analyzing real market transactions related to ES or to indirect related markets (e.g., travel costs of visitors to reach a natural park; technical abatement costs as an alternative to ES). Furthermore, expected consumer behavior in hypothetical markets can be estimated by willingness to pay concepts (Gómez-Baggethun et al. 2016). Due to the relatively high comparability, monetized values can be taken into account in economic decisions and contribute to an increased awareness of the social importance of nature (Brander and Crossman 2017). Additionally, it can lead to legal adjustments and “may contribute to address our inability, reluctance, or ideological intolerance to adjust institutions […] to our knowledge of ecosystems, biodiversity, and the human being” (Kumar et al. 2010: 292). Disadvantages of economic valuation are discontinuities in the pricing of ES, a lack of ethic economic guidelines (Gowdy et al. 2010), and the problem of transferring ES to conventional markets (Costanza 2016). Moreover, it lacks the consideration of complex, dynamic, and nonlinear relationships of ES as well as thresholds and tipping points (Kumar et al. 2010; Potschin and Haines-Young 2011).

Biophysical valuation is particularly relevant for process-based approaches and assessments of regulating services. It can be used to compare similar sites for one or multiple services but is less common in decision making. The special difficulty with the biophysical valuation is how to value ES beyond the accounting of ecosystem components, biotic functional traits, or ES (Gómez-Baggethun et al. 2016). Socio-cultural valuation is an umbrella term for valuation methods not based on biophysical or economic assessments. It is given greater consideration in recent literature valuing the cultural, therapeutic, artistic, inspirational, educational, spiritual, or aesthetic contributions of ecosystems. Besides, socio-cultural valuation offers the possibility to take up intrinsic and utilitarian values of nature (Kumar et al. 2010).

Despite the diversion in biophysical, economic, and socio-cultural valuation, the consideration of interlinkages, respective advantages, and disadvantages is necessary. For example, a biophysical value can represent more complex systems than an economic value, but the latter can be more effective in decision making. At the same time, a socio-economic value can reckon cultural aspects and individual desires. A separation of values is therefore not possible. Thus, the leading question of ES valuation should be “What is the relative contribution of, for example, natural capital to sustainable human well-being, in combination with other forms of capital (built, human, social) in a particular context?” (Costanza 2016: 20). The methodologies to value such complex interrelations are difficult to implement and require transdisciplinary collaboration and methodology (e.g., Daniels et al. 2018). Various uncertainties of the technique and limitations of measurement of socio-ecological systems have to be considered (Kumar et al. 2010).

2.2.2 Methods of Ecosystem Service Assessment

For an accurate valuation, a valid metric is needed. Over the years, methods for separated valuation have been developed. To apply ES methods, measurable indicators have to be selected. Indicators represent parameters that are proxies for ES. In TEEB, indicators were defined “as variables communicating something of interest or relevance to policy or decision makers with some logical connection to the object, or the process being measured” (Reyers et al. 2010: 116). Depending on the individual ES, indicators can achieve a precise measurement, e.g., crop yield as an indicator for crop provisioning. Especially for regulating services and cultural services, indicators can only describe more abstract proxies. For instance, a frequently used indicator for climate regulation is carbon sequestration and for cultural services the number of visitors in a park (Maes et al. 2014). Indicators can be distinguished in analyzing the ecosystem function or the generated benefit. It must be considered which step in the ES cascade is involved (Dunford et al. 2017). Suitable ES indicators should be selected by purpose, audience, position in the ES cascade, and availability as well as quality of data. Additionally, they should be spatiotemporally explicit, repeatable, and have a clear linkage to human benefit (Vihervaara et al. 2017). Following the ES cascade, in Fig. 3, some examples of ES with associated indicators are listed.

Fig. 3

Examples of ES following the cascade model and associated indicators (own figure based on Maes et al. 2016: 190)

In ES research, models either analyze the environmental aspects that are fundamental for the supply/demand or model ES themselves. It is prevalently discussed how far an assessment of the ecosystem condition should be included beyond ES measurements (c.f., MEA 2005a, 2005b; TEEB 2010). Ecosystem condition can be defined as “the overall quality of an ecosystem unit in terms of its main characteristics underpinning its capacity to generate ecosystem services” (Potschin-Young et al. 2018: 18). A condition assessment considers physical, chemical, and biological conditions as well as anthropogenic pressures (Erhard et al. 2017). Problems of condition assessments are, for instance, that there is no clear distinction to the ES potential and that there are difficulties due to lack of knowledge about the interrelationships (Erhard et al. 2017; Rendon et al. 2019). Depending on the purpose, a variety of methods can be used individually or combined to assess ES. In Fig. 4, a spectrum of existing methods is outlined, based on the EU OpenNESS project and examined by Harrison et al. (2018). The methods are aimed at either sectoral valuation or combined approaches, which are marked in the respective colors. In the following section, some biophysical and integrated models will be further described. A challenge for the future is to integrate, map, and predict biodiversity in a meaningful way using existing approaches.

Fig. 4

Schematic spectrum of rough method groups with illustrated interrelations (own simplified representation of the original figure by Harrison et al. 2018). Colors symbolize assignments to valuation divisions

2.2.3 Modeling and Mapping of Ecosystem Services

Spatial ES assessment approaches can either be represented as maps or conducted through mapping. Therefore, direct and indirect biophysical methods are commonly applied. The methods have criterion-specific opportunities and limitations. For the biophysical and integrated analysis methods, focused hereafter, characteristics are summarized in Table 1.

Table 1 Criteria for selecting different (biophysical) methods after Harrison et al. 2018. X = key item, * = possible item, ~ = rare item, + = only relevant if integrated with other ES modeling/mapping techniques

Biophysical ES assessments leverage existing biophysical models such as (1) ecological models (e.g., species distribution models—SDMs), (2) hydrological models (e.g., Soil and Water Assessment Tool—SWAT), (3) soil erosion models (e.g., Revised Universal Soil Loss Equation—RUSLE), and (4) state-and-transition models (STMs). In addition, agent-based modeling is viewed as a biophysical model. Agent-based models examine human or organizational interaction levels in relation to decision-making processes (Harrison et al. 2018). Biophysical valuations can be derived by the (social) valuation of final outputs, such as the pollution level of (drinking) water. The data for biophysical models is collected through direct measurements (e.g., field observations) or through indirect measurements. The latter include remote sensing and earth observation, socio-economic data, proxy indicators, and expert-based, statistical, or process-based methods of ES assessment (Vihervaara et al. 2017). Examples of remote-sensing data applied as ES indicators are land use and land cover (LULC), NDVI (Normalized Difference Vegetation Index), water layers, and primary production (e.g., Vihervaara et al. 2017). Remote-sensing and earth observation data provide advantages such as the high spatial coverage as well as regular updating with various spatial resolutions (de Araujo Barbosa et al. 2015). Thus, the heterogeneity within the LULC classes can be taken into account. Most commonly, remote sensing is used to quantify temporal changes in ES. de Araujo Barbosa et al. (2015) noted that the temporal extent of studies focused on single-digit time spans and primarily utilized land cover data. The application of remote-sensing data in ES models is still not widespread, especially in Europe (c.f., de Araujo Barbosa et al. 2015; Campagne et al. 2020).

Integrated ES assessment models combine various sectoral models and are explicitly designed to quantify the results for decision-making purposes (Dunford et al. 2017). Bayesian Belief Networks (BBNs) set likelihood relationships between input parameters (in the case of ES, factors that influence supply such as land cover or soil types) and possible outputs (such as ES supply, demand, or benefits). One advantage of the model is that multiple methods can be considered. Furthermore, the model uses deterministic uncertainty values due to its conditional approach. Multi-Criteria Decision Analysis (MCDA) is often recommended for non-monetary valuations (Kumar et al. 2010; Potschin and Haines-Young 2011; Gómez-Baggethun et al. 2016). MCDAs are flexible approaches to assess trade-offs of multiple ES in different scenarios and to filter out the best possible decision. For this purpose, the relative relationships are examined in terms of economic, social, and environmental impacts between as many parameters as possible (Dunford et al. 2017). However, a big challenge of MCDA lies in the determination of weights for the different criteria.

Mapping approaches have the advantage of providing comprehensible results that distinguish ES supply and demand areas. They are applied for three overarching purposes:

• Simple look-up tables for an overview of ES, using LULC as an approximation of ES

• Quantification of ES by spatial methods in varying complexity and combining literature, expert knowledge, statistics, and quantitative or qualitative field data

• Representation of spatial results of models (e.g., GIS processing of integrated assessment models).

LULC is fundamental for many assessment methods. Versatile information on supply, flow, and demand can be derived from the data through the approximation of ES by ecosystems and change detection (e.g., Burkhard et al. 2012). Existing LULC datasets as well as remote-sensing data can be used. In the European ES assessment, the CORINE land cover (CLC) was applied (Maes et al. 2013, 2020). The CLC is based on Copernicus and currently available for the years 1990, 2000, 2006, 2012, and 2018. The minimum mapping unit is 25 ha (EU 2021). The major critique of the method is the comparably low spatial resolution and neglected heterogeneity within classes (Eigenbrod et al. 2010). Moreover, insufficient timeliness and non-consideration of all occurring ecosystem classes were criticized (Maes et al. 2020; Perennes et al. 2020). The application of LULC data is particularly suitable for ecosystems that are strongly influenced by humans as the ecological heterogeneity is usually lower in these systems, for example, due to the selection of plant species or water management interventions (Perennes et al. 2020).

For mapping implementations, a further distinction can be accomplished in (1) common GIS analysis applications, (2) transferring of biophysical models, and (3) integrated GIS modeling tools explicit for ES assessment. The first implementation includes the matrix method, the classification of ES supply, flow, or demand per LULC (c.f., Sect. 2.2.4). The second method focuses on the analysis of individual ES with biophysical models. The third is designed for interrelations, trade-offs, and scenarios. Most popular examples of integrated GIS modeling tools are InVEST (Integrated Valuation of Ecosystem Services and Trade-offs), ARIES (ARtificial Intelligence for Ecosystem Services), MIMES (Multiscale Integrated Models of Ecosystem Services), and Solves (Social Values for Ecosystem Services) (Palomo et al. 2017).

A tiered approach was developed in order to map ES purpose-specific and comparable to other ES assessments (Fig. 5) (Grêt-Regamey et al. 2017). Tier 1 maps encompass, for instance, look-up tables as described previously. ES supply and demand are quantified by proxy indicators based on existing datasets. Tier 2 maps build on the same principle, but link several indicators related to LULC data, for instance, socio-economic or biophysical indicators. Tier 3 maps apply biophysical, integrated, and ES-specific models to achieve a further level of accuracy (Maes et al. 2014). One can recognize that tier 1 maps offer comprehensive overviews, while tier 2 and 3 maps provide more credible results, but require a greater amount of time and data (Maes et al. 2016).

Fig. 5

Decision tree to choose appropriate ES mapping tiers (own representation of the original figure by Grêt-Regamey et al. 2017)

2.2.4 The Matrix Approach

Exemplarily, a matrix approach is described in the following, which will be used in Sect. 3 for the case study of ES assessment in the Rhenish mining area. In contrast to previously described methods, the matrix method targets a general approach to compare the potential, flow, and demand of ES between different biophysical entities via commonly tier 1 maps. The approach is based on Burkhard et al. (2009, 2012, 2014) and has been applied, discussed, and improved in various case studies (Campagne et al. 2020). The approach is based on the supply–demand concept that conforms with the first to fourth step of the cascade model (Burkhard et al. 2014). In the matrices, ES are plotted against geophysical units (Burkhard et al. 2012). Burkhard et al. (2014) applied CLC classes as geophysical units and a classification of ES based on the authors’ own compilation (for a detailed list, see Burkhard et al. 2014). The intersections represented the potential, flow, or demand for one ecosystem service within a spatial unit, depending on the purpose of the matrix. The intersections were specified on a relative scale from zero to five (0 = no relevant capacity, 5 = very high relevant capacity). The values could be determined by different qualitative and quantitative methods, whereby in the matrix of Burkhard et al. (2014) these were mainly based on expert knowledge.

Campagne et al. (2020) reviewed the further development of the matrix approach (2009–2019). The number of studies applying the approach has significantly increased over time with a focus on ES supply (Campagne et al. 2020). Fields of application are, for example, (1) data-scarce areas, (2) the assessment of specific ES or specific geophysical units, (3) impact analyses of spatiotemporal changes, and (4) ES assessment-orientated studies (see Campagne et al. 2020). In reviewed case studies, more than half of the matrix values were determined by literature data transfer, where previously published matrices were applied or values were created by information from scientific literature (Campagne et al. 2020). In Table 2, the potential and the limitations and uncertainties of the matrix approach are listed. The approach by Burkhard et al. (2014) has been repeatedly adjusted considering the mentioned limitations.

Table 2 Potentials, limitations, and uncertainties of the matrix approach; based on Burkhard et al. (2014), Jacobs et al. (2015), Campagne et al. (2020), Müller et al. (2020)

Müller et al. (2020: 14) designed a modified matrix for northern Germany on an annual temporal basis which “must be comprehended as a strongly generalized regional prototype, which should be modified and adapted for the respective demanded case study conditions.” Compared to the approach by Burkhard et al. (2014), the considered ecosystems and landscape structures were enhanced, the possibility of a complementary assessment of ecosystem conditions was enabled, an adapted scoring system was provided, and an uncertainty assessment was included (Müller et al. 2020).

Since 2009, the method has been refined through expert consultations, case studies, and consideration of the scientific discourse (Müller et al. 2020). The matrix focused on the ES potential. A significant change to the approach by Burkhard et al. (2014) is that the scores were weighted between 0 and 100 points. Although the 0–5 scaling had the advantage of emphasizing the qualitative ranking character, the new score offered the possibility to highlight potentials in a more differentiated way—and, thus, better allow local adjustments (Müller et al. 2020).

In Sect. 3.3, a first assessment of ES potentials in the Rhenish mining area has been conducted utilizing the matrix approach and building the foundation of further necessary investigations. The matrix approach can be used as a first step to a more holistic assessment of ES in mining areas but also other landscapes, which has to include a quantification, e.g., biophysical, aesthetical, monetary, etc., of the individual matrix elements.

3 Ecosystem Services in the Rhenish Mining Area

For more than a century, lignite has been mined in the Rhenish mining area. Today, the three open-cast mining sites of Inden, Hambach, and Garzweiler form the largest German lignite mining region. Over the decades, the cultural landscape has been shaped by the spatial influences of disturbance and reclamation. But reinforced by the German lignite phase-out, a sustainable and prompt transition to a post-mining region is now required. While in Sect. 2 the concept of ES in general was introduced, the large-scale spatial assessment provides various, but still little widespread, opportunities as framework for the transformation of mining areas. The terms and conditions of the scope are outlined by applying the matrix method to the transformational landscape of the Rhenish mining area.

3.1 Research About Ecosystem Services in Mining Areas

In the MEA (2005b), mining is mentioned as one major business activity in conflict with other ES beneficiaries. The mining principles of the International Council on Mining and Metal (ICMM 2020) state as part of their sustainability principles to assess impacts and risks to ES and biodiversity. This is addressed by the implementation of a mitigation hierarchy with the objective to achieve no-net-loss of biodiversity (ICMM 2020). The latter applies to new projects or major expansions of existing projects. The ES recognition by the ICMM in politics, spatial planning, and public suggests that the ES concept can be a valuable concept to assess the cumulative impact of mining activities and initiate political as well as economic responses (Assumma et al. 2022).

Open-cast mining exhibits a strong impact on geomorphology, soil formation, biodiversity, water balance, ecosystems, and cultural landscapes (Gerwin et al. 2023). The socio-ecological and socio-economic structure of a region is changed in the long term (Zerbe 2019). One of the unique features of lignite mining areas is their extensive pit size. Some common impacts on ES are (1) soil erosion and loss of soil ES, (2) deforestation, (3) destruction of ecosystems, habitats, and biodiversity, (4) acid drainage, (5) emissions and noise, (6) landscape degradation, and (7) loss in social ES (Imboden and Moczek 2015; Zerbe 2019; Assumma et al. 2022). In contrast to the negative impacts, open-cast re-cultivated post-mining areas can provide versatile, valuable biotope mosaics (Kirmer and Tischew 2019), and high-potential cultural landscapes (Zerbe 2019).

Based on Boldy et al. (2021) and Assumma et al. (2022), the number of articles that deal with ES in mining contexts is small compared to the rest of ES research. While in the mining context mainly economic methods were applied (e.g., benefit transfer, willingness to pay, and total economic value), the biophysical assessment is in the center of research (Assumma et al. 2022). However, the analyzed examples differ substantially in the applied ES concepts and methodologies. ES assessments, mostly focused on coal, lignite, or metal extraction sites (Boldy et al. 2021), were applied to quantify the cumulative impact of active mining operations and to measure the possible effects of reclamation (Assumma et al. 2022). Overall, positive changes in ES were associated with the post-mining efforts (especially regulating services) and negative impacts with the active mining phases (especially provisioning services) (Boldy et al. 2021). The eight most frequently examined services were carbon sequestration and storage, erosion prevention and maintenance of soil fertility, food, raw materials, waste-water treatment, fresh water, moderation of extreme events, and recreation and mental and physical health (TEEB classification) (Boldy et al. 2021). Boldy et al. (2021) recommended to conduct further research to achieve comparability through the establishment of consistent definitions, classifications, and assessment methods. Moreover, the analysis of the full ES delivery chain and development of biodiversity is needed including potential, flow, and demand of long-term mining effects on ES.

3.2 The Rhenish Mining Area

The Rhenish mining area designates the lignite mining region located in the Lower Rhine Bay in North Rhine-Westphalia, although there is no uniform spatial delineation. In this work, the Rhenish mining area is delimited by administrative units. The counties of Rhein-Kreis Neuss, Mönchengladbach, Heinsberg, Rhein-Erft-Kreis, Düren, Euskirchen, and the district of Aachen are structural parts of the Rhenish mining area. Chosen as the study area, the core area is limited to 20 municipalities surrounding the open-cast mines of Garzweiler, Inden, and Hambach and including re-cultivated areas of former mining sites. While many affected and interrelated ecosystems are considered, adjacent landscape units such as the Eifel are almost excluded. Figure 6 maps the delimitation of the area with an extent of 1518 km².

Fig. 6

Rhenish mining area with the three open-cast mining sites of Garzweiler, Hambach, and Inden

The Lower Rhine Bay is part of the North German plain characterized by Pleistocene terraces, glacial, fluvioglacial and periglacial processes, and loess sediments (Goetzke 2011). The dominant soil type is Luvisol. Concise natural main units are the Jülich and Zülpich Börde as well as Ville and the Cologne Bay in the east (LÖBF 2005). Moreover, the area includes a small section of the North-West Eifel in the southwest. The Rur and the Erft are the major rivers in the Rhenish mining area. The Rur intersects the Jülich Börde between the open-cast mines Inden and Hambach. The Erft flows eastward into the Jülich Börde along the cities Kerpen, Bergheim, and Grevenbroich. High tertiary lignite resources have enabled the mining in the Lower Rhine Bay since the middle of the nineteenth century (Goetzke 2011).

The region is highly influenced by anthropogenic land use. The total population comprises around 882,000 inhabitants. The municipalities of Mönchengladbach (260,276 inhabitants), Düren (91,350), Bergheim (65,968), Grevenbroich (64,381), Kerpen (61,791), and Hürth (59,602) are the most densely populated (census: June 2021, IT.NRW 2021a). Highways cut the area with an average daily traffic above 60,000 motor vehicles per 24 h in some sections (census: 2015, IT.NRW 2021b).

In the Rhineland, lignite mining has started in the eighteenth century with small pits in Ville. As the industrialization progressed, mining increased. In the twentieth century, reorganization, rationalization, and merger led to a reduction of open-cast mines from 23 in the 1950s to 8 in the 1980s, hand in hand with increasing extension of the remaining mining sites. In the 1990s, further concentration was carried out on the current three mining sites of Garzweiler, Hambach, and Inden (Pflug 1998).

Today, the open-cast mines are 14.8 km² (Inden), 44.2 km² (Hambach) (both December 2021), and 20.7 km² (Garzweiler) (October 2021) in size (according to ATKIS Basis-DLM). In total, the mining sites take up about 5% of the area. The additional land taken up by operational areas, traffic areas, power plant areas, and dumpsites must also be regarded. In 2020, in the Rhenish mining area 306.2 million m³ of overburden were processed and 51.4 million tons of lignite were extracted (Statistik der Kohlenwirtschaft e.V. 2021). The maximum depths of the operating open-cast mines are 470 m in Hambach, 230 m in Inden and 210 m in Garzweiler II. With the German lignite phase-out law, reductions in the mining period and downsizing of the originally approved areas have been initiated, in particular for Garzweiler II and Hambach (LANUV n.d.b). The end of the lignite extraction is currently scheduled for 2029 and 2030 for Inden and Hambach and for 2038 for Garzweiler (LANUV n.d.a).

Most effects of open-cast mining on ecosystems and biodiversity in the Rhenish mining area are disturbances by deforestation, the effects on soil structures, and the interference of the water balance (Zerbe 2019; Gerwin et al. 2023). In addition, psychological effects of displacements, protest movements, and distinct cultural landscapes indicate a strong connection to the area and related (cultural) ES (Imboden and Moczek 2015). In the context of the 1.5-degree target of the Paris Agreement, the amount of lignite mined portrays another important position (c.f. Rieve et al. 2021). To what extent the exposition of carbon dioxide has to be considered within the ES approach, e.g., as demand, is not covered extensively in literature. However, re-cultivation efforts provide a variety of ES. Examples are the Sophienhöhe at the northern edge of the Hambach mine, as well as the re-cultivated forests in the municipalities of Hürth, Ville, and Brühl. Ville and Brühl are located southeast of Hürth, outside of the study area. Here, the landscape has been re-cultivated for one century. A productive broad-leaved forest (ES: timber, diverse regulating and cultural services), an artificial lake landscape (ES: diverse regulating and cultural services) as well as habitats for endangered animal species (e.g., Bechstein's bats) (ES: genetic material, cultural services) have developed there (Zerbe 2019).

Figure 7 shows the LULC map of the Rhenish mining area. Particularly striking in the illustration of the LULC pattern is the dominance of the agricultural areas of the Jülich and Zülpich Börde as well as the three open-cast mines. Small settlements and traffic facilities dissect the area. Several highways can be recognized as well as the railroad line between Cologne and Aachen, running in the southern parts and passing through the city of Düren. Dense areas are primarily located in the periphery: in the north the city of Mönchengladbach, in the south Düren, in the southwest Eschweiler, and in the east Hürth and Frechen. Only some central parts of the cities have a building coverage greater than 50%. Forested areas mark the northern Eifel extensions western of the city of Düren. These reveal the most coniferous forest share within the study area. The courses of the Inde (east of the open-cast mine Inden) and the Erft (east of the open-cast mines Hambach and Garzweiler I) can be identified well by the riverside as small-scale and contrasting structure of LULC elements. Along the linear structures of settlement-related objects, smaller natural landscape elements and diverse ecosystems are located.

Fig. 7

Land use/land cover map of the Rhenish mining area. The classification of LULC types was performed in accordance to Perennes et al. (2020) based on the ATKIS object catalog (AdV 2011). ATKIS Basis-DLM is provided under the data license Germany—Zero—Version 2.0

Unlike the residential areas, industry and commerce form large-parcel elements, mostly adjacent to the settlements or open-cast mines. Smaller and abandoned mining pits are classified as industrial land use, recognizable by larger and undissected patches. These include the west-rounded industrial areas in the northwestern quarter of the area near the Erft river, which are former operating sites of the Garzweiler I and the Fortuna-Garsdorf open-cast mines (north to south). Other large-scale industrial areas can be assigned to power plants and refining plants: Frimmersdorf (east of Garzweiler I), Neurath (southeast of Frimmersdorf), Niederaussem and Fortuna-Nord (south of Neurath, north of Bergheim), Wachtberg (southwest of Frechen), Knapsacker Hügel/Berrenrath (southwest of Hürth), and Weisweiler (southwest of Inden).

The western edge of the Garzweiler II open-cast mine is classified as sparsely vegetated area. It can be interpreted as near-future extraction sites or might already be excavated partially since the last LULC update. In contrast, sparsely vegetated areas south of Garzweiler I can be described as closed open-cast sites in an early stage of re-cultivation. Similar areas can be found in the western margins of the Inden mine. In the vicinity of the Hambach mining site, the artificial elevation of the Sophienhöhe can be distinguished. LULC at the Sophienhöhe is mainly classified as mixed forest with small water areas, meadows, bushes, and recreational uses. The remnants of the Hambach Forest, as deciduous and mixed forest, are visible at the southeastern break-off edge. The landscape strip eastern of the Erft is characterized by heterogenous structures of agricultural land as well as deciduous and mixed forest. The area is influenced by former mining. Many patches are forestry or agricultural re-cultivated landscape elements. The same applies to the deciduous forest, water bodies, and agricultural areas in the municipality of Hürth. Overall, the coverage with forests and near-natural ecosystems compared to other land-use classes is very small.

3.3 Ecosystem Services Potentials Based on Land Use in the Rhenish Mining Area

The ES potential can be estimated by means of land-use classification. As example of a qualitative approach an ES potential matrix (shown in Fig. 8) is applied on the different land-use types in the Rhenish mining area. The applied matrix is based on the design by Müller et al. (2020) (matrix version 6.1) as well as Perennes et al. (2020). Uncertainties of the transfer of expert-based valuation from Northern Germany to the region were recognized and quantified, but not discussed here due to the exemplary character of the approach.

In particular, the matrix by Müller et al. (2020) was applied, whereby missing values of landscape elements were adopted from Perennes et al. (2020). The ES potential matrix was built by listing land-use classes on the x-axis and representing ES on the y-axis. Only provisioning, regulating, and cultural services were considered in line with CICES. To highlight the qualitative character of the results, the matrix values were defined in the original zero to five range of Burkhard et al. (2014). Therefore, the values by Müller et al. (2020) were normalized as decimal values to this scale, following Perennes et al. (2020). The value ‘0’ indicates no significant potential. The value ‘5’ denotes the highest potential in this matrix. The ES potential matrix is plotted in spatial distribution as Fig. 9. All originally included ES in the matrix by Müller et al. (2020) except for beach wrack, flotsam organic material were applied here. In total, values for thirteen provisioning services, eleven regulation and maintenance services, and six cultural services were transferred. Within the provisioning services some abiotic ecosystem outputs must be differentiated, encompassing ornamentals, drinking water, abiotic energy, and minerals. These were considered, either because of the significance to the study area or due to the common classification as ES. ES, which were not included but can be of further interest, are such as genetic material or mediation of annoyances of anthropogenic origin such as smell or noise. For some others, a subdivision could be of interest, for example, water usage for drinking or non-drinking purposes (c.f., Haines-Young and Potschin 2018).

In many studies, the selection of the single ES is not reproducibly described. The implementation of the ES potential matrix can provide an alternative way to identify relevant ES or ES-related patterns via a qualitative assessment. Here, the implementation targeted at enabling a comprehensible starting point for future ES assessments in the Rhenish mining area.

The matrix in Fig. 8 in combination with land-use data of the investigated area can provide useful qualitative information on the current potential supply of ES. It certainly cannot quantitatively account for actual supply of the individual ES as the complexity of different site conditions was not considered. But it can give a first overview on the spatial distribution of different ES and, thus, be aligned with information on spatially explicit data on ES demand. The approach can also provide a useful method for the qualitative estimation of future ES due to land-use change by landscape transformation. Figure 9 gives examples of the spatial distribution of ES potentials of current land-use types for provisioning, regulating, and cultural services. The expert-based estimations of respective ES potentials were mapped for LULC classes by their matrix values. The assessment does not provide information on future potentials, which needs to be a next step as also ES demands are considered.

Fig. 8

Ecosystem service potential matrix for the Rhenish mining area (own figure based on values from Müller et al. (2020), Perennes et al. (2020)). Darker green indicates higher potential. *abiotic ecosystem outputs, **modified LULC class, ***aggregation of natural and artificial waters

Fig. 9

Examples of provisioning service potential (top row), regulating service potential (center row), and cultural service potential (bottom row) in the Rhenish mining area

Basic patterns become apparent, identifying areas with high overall potential or for specific ES. In addition to the overall spatial distribution of ES potential, also small-scale heterogeneity of the study area can be assessed (not shown here). Spatially predominant LULC objects were identified as arable land, urban fabric, and active open-cast mines. Moreover, the heterogeneous linear structures along water bodies and re-cultivated mining areas were recognized as regions of structural interest. Open-casts, industrial and heavily sealed areas, dumps, and traffic facilities display the lowest ES potential in the area. Key areas of high potential are dedicated to forested patches. Provisioning, regulating, and cultural services are differently pronounced, but a detailed description is not provided here.

Overall, the distribution of ES potentials indicates deficits for a sustainable landscape. This is due to the historical development as a highly productive agricultural area as well as open-cast mining operations with grave impact on the natural environment. For the overall ES potential, the LULC dominance of agricultural areas is decisive. The open-cast mines cause large areas without or with very low ES potential and thus strongly reduce the overall potential. Re-cultivated areas are of special interest as many productive agriculture and forestry sites are included. As providers of high potentials, re-cultivated forests and near-nature elements stand out from overall potential. However, the destruction rate of lignite mining on previous natural areas and forests needs to be considered as well. The remaining areas of the Hambach Forest indicate that today's open-cast mining areas have rendered areas that previously had high potentials to be now nearly irrelevant. The evidence is in line with the current scientific knowledge on ES in mining areas. However, the question about the condition of mapped ecosystems and the subsequent influence on ES arises. Condition analysis is of major interest in current ES research, acknowledging significance of condition for ES potential and supply (c.f., Maes et al. 2020). By disregarding condition indicators, the validity of results for the actual supply is limited. Open questions are, for example, to what extent re-cultivated forest areas have the same potentials as previous ones, or which maturity phase can be considered equivalent to remaining forests in the context of a matrix assessment. Furthermore, condition assessments are essential for determining the potential of agricultural lands. In order to achieve more accurate conclusions, indicators such as cultivation, soils, hydrologic factors, and quality of biodiversity need to be regarded in greater detail. In addition, impact gradients of disturbances need to be considered such as possible contamination, noise, or smell occurring in the vicinity of industrial and mining elements. Possible impacts on surrounding LULC patches limit the ES potential estimation.

Up to date, no statements about the value of ES in the Rhenish mining area can be made due to the lack of knowledge on spatial supplies and demands. Without quantification or alignment with established values, e.g., yield rates or pollution, valuation is only possible in a comparative way. By determining ES demand, initial qualitative statements could be drawn about the potential-demand balance, enabling conclusions about unmet needs or surpluses. In relation to ES demand, provided potentials can be estimated as adequate or inadequate. For instance, agriculture requires higher potentials for regulating services such as pest and disease control and nutrient regulation (Burkhard et al. 2014). Only statements can be made about which regions of the study area or which patches might be more relevant for ES supply than others. Moreover, the reducing effects of the open-cast mining areas and industrial sites can be spatially highlighted, as well as positive effects by re-cultivation, considering still changed ES supply compared to previous states. ES especially affected by these spatiotemporal processes might be more relevant to assess than others. Furthermore, the scarcity of ES in the study area is obvious. Examples are minimal examined potentials for, e.g., livestock and flood protection. However, if these are significant, cannot be answered since even low potential might be sufficient if demand is similarly low.

3.4 Recommendations for Future Studies

The outlined example illustrates the purpose and opportunities of qualitative ES assessments by simple look-up maps. For a better estimation and validation of the impact of ES in the Rhenish mining area and for the general implementation on mining regions, a quantification, e.g., biophysical, aesthetical, monetary, etc., of the individual matrix elements is necessary. Overall, a quantification of the potential and an assessment of the supply need to be carried out in order to obtain a valid picture of the specific mining area. For this purpose, a combination of standalone and integrated methods, summarized in Sect. 2, can be used to develop comprehensible qualifications and conclusive evaluation methods. In addition, in this work only the potentials were considered as an example. For a full picture, an assessment of potential, supply, flow, and/or demand is needed, depending on the specific purpose and circumstances of the case study. To prevent misinterpretation in qualification models, reduced uncertainties in matrix values, improved comparability, and continued efforts in standardization of ES definitions and classification are needed. Quantification of matrix values can be implemented, in particular, by using biophysical models. In addition, an equivalent determination of the values of cultural services is necessary. While these are neglected in many assessments of ES, they represent important services for physical and mental health in cultural landscapes. Moreover, a spatial and temporal explicit processing of the matrix can be achieved through ongoing quantifications and revisions specific to the study area, leading to a more accurate overview and general improvement of the matrix implementation.

One key area of content can be the influence of open-cast mining areas on regulating and cultural services. Of particular interest are spatiotemporal developments by different stages of the lignite mining industry cycle and contrasting disturbance-reclamation rates. ES valuation of the supply–demand balance can contribute to an appropriate selection of different re-cultivation measures and spatial planning. Decisive to the evaluation is a development of applicable and meaningful condition assessments. ES-based scenarios offer the possibility to model the aspired biophysical impacts. Thus, sustainable planning steps for a livable environment can be introduced adapted to the regional socio-ecological circumstances. In addition, ES impacts by open-cast mining to agriculture represent opportunities to investigate the linkages between condition, provisioning services, regulating services, and biodiversity in more detail.

4 Mechanisms of Pricing, Budgeting, and Pathways for Decision Making

Both in science and in the public, the concept of ES is broadly accepted. It can hardly be denied that the concept of ES can contribute positively to the conservation of natural ecosystems. This is especially true if the conservation of biodiversity is given a high priority. Approaches to further develop biodiversity conservation and optimization of ES together are complex and need to be carefully evaluated (see also Mace et al. 2012; Reyers et al. 2012). In addition, it can be assumed that the concept of ES does have strong support from the broad public. However, when real-world decisions are to be made, it always becomes problematic when individual interests are affected by the protection and expansion of ES, especially when the decision-making process is fragmented, i.e., it is composed of a sequence of many individual decisions. Often, the individual interests prevail, which means that the desired levels of ES are not achieved. Ultimately, this problem is due to the fact that ES have the character of public goods, where it is almost impossible to price them at their true economic value. This problem is exacerbated when decisions are made on the basis of basic economic data, since ecological aspects are generally not considered at all here, i.e., they are assigned a value of zero.

One of the main reasons for the often inadequate inclusion of ES is the lack of information on their benefits on the one hand and the inadequate structuring of relevant decision-making processes for this purpose on the other. This chapter will shed some light on these shortcomings. The next section addresses the economic pricing of ES, helping to improve the information base. In this context, it is of particular importance that ecological and economic information are combined. This is neither in line with established practice nor do market prices exist for the services to be evaluated, which makes economic pricing of ES challenging. Subsequently, the structuring of the decision-making process is examined. Section 4.2 examines budgeting, a well-established tool used by companies to manage the target-oriented provision of resources. Section 4.3 looks at the structuring of the decision-making process and the necessary involvement of the relevant stakeholders.

4.1 Economic Approach to Consider ES: Pricing Externalities

Economic information plays an essential role in many decision-making situations. This applies both to the resources provided in the context of budgeting processes and to the calculation of the benefits of a decision based on attributable revenues. At the same time, it has been known for many decades that there are relevant costs that decisions do not take into account. These are so-called external costs or externalities, which are borne neither by the producer nor the consumer of a good. Not taking such external costs into account regularly leads to market failures, since third parties are harmed by such decisions and are usually not compensated. Climate change is a good example of such external costs. For decades, electricity was generated almost exclusively with the help of fossil fuels, which was associated with high carbon dioxide emissions. The accumulation of carbon dioxide and other greenhouse gases in the atmosphere then caused climate change, which has very serious negative consequences for the livelihood of many people and for the functioning of many ecosystems. As a result, there are high losses of income, e.g., in agriculture and forestry. The frequency of extreme weather events is increasing and these cause damages to the inhabited and uninhabited environment and people living there. Whole ecosystems are changing with severe consequences for the provision of various ES and biodiversity. An example is the melting of ice sheets, which leads to a rise in sea level and endangers coastal areas worldwide.

For these reasons, policymakers around the world have agreed to substantially reduce greenhouse gas emissions. In the EU, an emissions trading system was introduced as early as 2005 that prices greenhouse gas emissions in order to internalize the external costs incurred. After initially very low prices for permits for carbon dioxide emissions, 1t of CO₂ now costs around €80. Even this price is still considered by many experts to be significantly too low. The German Federal Environment Agency, e.g., considers a price of just under 200 €/t to be appropriate to cover the damage costs of CO₂ (Matthey and Bünger 2019). Prices of more than 400 €/t are even being discussed (Luderer et al., 2018). When such prices are incorporated into energy system models and related decision-making processes, it quickly becomes apparent that renewable energy not only leads to significantly lower external costs, but also represents the best option in macroeconomic terms. The internalization of external costs can therefore be seen as an important innovation driver for the transformation of numerous value chains and markets. In this vein, the internalization of external costs can be seen as a driver for economic and behavioral changes for economic and political decision-making.

The transfer of the external cost approach to ES leads to a further increase in complexity. While resource consumption and emissions are based on measurable flows of materials that only have to be priced, the evaluation of ES requires the consideration of complex cause-effect relationships, specifically when biodiversity is taken into account. One of the first approaches originates from Hein et al. (2006) (Fig. 10). Following the methods of lifecycle assessment, they first propose the definition of system boundaries in order to quantify the ES provided. This is in effect a biophysical quantification that provides the basis for subsequent economic valuation. In the next step, the quantities of ES are priced either in monetary terms or within the framework of scoring models, i.e., through other indicators. In this way, it becomes possible to aggregate the total value of an ES including the preservation or expansion of biodiversity and subsequently, by aggregating the values of all ES, also to determine the overall value of an ecosystem.

Fig. 10

Ecosystem and biodiversity valuation framework (own figure after Hein et al. 2006)

Even if this approach is plausibly constructed, it is both incomplete and complexity-reducing. For example, it does not provide suggestions on how to meaningfully incorporate the complex cause-effect relationships in ecosystems, nor does it include higher-level aspects such as increasing or decreasing biodiversity. Furthermore, purposeful approaches must clearly highlight the problem of frequently insufficient data as well as the inclusion of uncertainties with regard to the underlying cause-effect relationships (Sagoff 2011). At this point, for reasons of space, it can only be stated that such evaluation approaches still face considerable challenges and will certainly be further developed in the future (see also Gowdy et al. 2010).

Even if the challenge of pricing external effects is still unsolved, it makes sense to use monetary values (or sometime scores) for different ES, as otherwise there is a risk that these will either not be considered at all or only as a secondary consideration in decisions. Ultimately, it is not a matter of exact values—which are not given even in the case of (often volatile) market prices—but rather of the inclusion in the discussion about the best possible decisions. Such pricing approaches (based on the monetary valuation of ES) also make it possible to make controversial views on the valuation problem visible. However, being aware of the underlying methodological problems, it is reasonable to combine other approaches with the economic pricing of ES. In this context, budgeting approaches are increasingly discussed in order to avoid fragmented decision-making processes to the detriment of the maintenance and provision of ES. Involving various stakeholders is also a promising avenue of placing importance on ES in transformation processes such as in in the Rhenish mining area. Both aspects are discussed in more detail in the following two sections.

4.2 Budgeting

Budgeting is a term established in management and controlling that deals with the allocation of (often financial) resources to an organizational unit, a project or to achieve a goal (Lalli 2012). The budget managers can dispose of the budget within certain limits in order to achieve the goals in their area. Budgeting is often based on a top-down approach in which the total available resources are distributed among different areas. In this way, a balanced allocation of capacities and resources is ensured in the sense of implementing the corporate strategy. This is in contrast to bottom-up approaches, where resources are allocated according to the arising opportunities as well as the persuasive power of individual organizational members. Such pure bottom-up approaches often lead to fragmented decision-making processes in which (strategic) goals can often no longer be pursued as a whole.

With reference to the transformation process in the Rhenish mining area, such fragmentation tendencies cannot be ruled out. Here, too, many actors are (rightfully) involved and decision-making processes are often distributed over the timeline in a small-scale manner. This leads to the fact that, on one hand, decisions are repeatedly made in favor of short-term economic advantages and that, on the other hand, complex and higher-level aspects such as the long-term provision of ES are neglected. Therefore, we advocate for a budgeting approach that establishes land-use plans that balance long-term and short-term interests, based on sustainability goals and the levels of ES to strive for.

A first step would be to define a long-term strategy for the transformation process in the Rhenish mining area and then to define the associated objectives. Corresponding land-use plans could then be derived from this, specifying, for example, what proportion of land should be left in a near-natural state and how agricultural land can be farmed, considering the provision of ES, and how the recreational function of the landscape can be guaranteed. In this sense, the available area would be budgeted, i.e., divided according to land-use types and the ES to be provided or demanded as a result. Such an approach would provide an overarching level for all landscape planning decisions. This would also reduce the danger of fragmented decision-making processes, in which nature-oriented uses are increasingly marginalized in the end.

Such a budgeting approach would, thus, directly address the strategic level and the goals derived directly from it. However, this is by no means intended to avoid the participation of numerous stakeholder groups, but on the contrary: They should be involved at the strategic level from the very start, in order to achieve an early consensus on different types of land use. This will also allow the provision of ES to be given a higher priority, especially when the value of such services is considered in the related decision-making processes. A participation-oriented budgeting approach can thus better ensure the preservation and expansion of ES in the context of transformation processes. Facets of the decision-making process required for this are described in the following section.

4.3 Structural Elements of the Decision-Making Process

A top-down approach does not mean that different stakeholder groups are not involved. On the contrary, they can play an essential role and contribute their expertise in the problem description, the definition of the system boundaries and the land-use strategy. They can also contribute to the success of the respective measures at the local level during (decentralized) implementation.

Figure 11 illustrates a possible structure of the decision-making process. The object of investigation is already defined together with all relevant stakeholders. These can be representatives of environmental organizations, the economy, politics, science, the media, affected citizens, and also future generations (Bogacki and Letmathe 2021). On the basis of the defined system boundaries, the most comprehensive data possible, including relevant cause-effect relationships, should then be collected. Here, all actors play an important role who can either provide data or assess their validity. The created data basis not only reports the actual state, but also creates a basis for the valuation of ES. In summary, this step allows to design a factual basis for the development of a land-use strategy that is as correct as possible and as needed for the specific purpose. Missing data and evaluation uncertainties should be clearly stated, so that deficits in content can be included in the discussion. The documentation and evaluation of ES provide a realistic picture of the current state of knowledge and, thus, form an important basis for the design of a land-use strategy, which also sets objectives for ES to be provided in qualitative and quantitative terms. Since normative questions are the primary focus here, all relevant stakeholder groups should again be included in the definition of strategy and objectives. Overall, these first three steps make it possible to combine normative interests and scientific facts in a meaningful way in order to achieve a good and objectively comprehensible balance of interests between the individual stakeholder groups. Subsequently, the land-use strategy serves as a guideline for deriving specific land-use decisions, which must then be guided by the corresponding budgeting and target objectives. The detailed planning should particularly involve local stakeholder groups in addition to the land-use planners involved. The higher level must then ensure complementarity with the land-use strategy.

Fig. 11

Decision-making process and involvement of stakeholder groups

The decision-making process described can address the problem of many fragmented decisions with suboptimal results. At the same time, it ensures that all relevant stakeholders are appropriately involved. It also enables a separation of scientific and normative aspects and can therefore facilitate discussions that allow to consider ES and their long-term value.

5 Conclusions

The concept of ES as a potential framework for socio-ecological transformation processes of mining areas toward sustainable post-mining landscapes was introduced using the example of the Rhenish lignite mining area in Germany. The role of regional biodiversity as a basic resource, which is essential for many ES, is undisputed. Despite their crucial contribution to human well-being, these services are only rarely considered in spatial and landscape planning decisions.

For a better estimation and validation of the impact of ES in mining areas, a quantification of ES, such as biophysical, aesthetical, monetary, etc., is necessary. Overall, the exemplary case study demonstrated how the assessment of ES potential can provide a valid picture of a landscape’s ES. For this purpose, the matrix method was applied to the Rhenish mining area and qualitative and quantitative methods that can be used (standalone or combined) to develop comprehensible and conclusive evaluation procedures introduced. In addition, the contribution of ES valuation to an appropriate selection of different re-cultivation and re-naturalization measures for spatial and landscape planning was explained. Hence, biophysical modeling using ES-based scenarios is critical to provide better decision support based on applicable and meaningful condition assessments. Moreover, sustainable planning procedures for a livable and sustainable environment can be introduced in regards to the regional socio-ecological situation.

In the Rhenish mining area, many ES potentials show deficits for a sustainable landscape due to the historical development as a highly productive agricultural as well as open-cast mining area with grave destructive impacts on the natural environment. Although, the Rhenish mining area currently shows high potentials for both food and energy provisioning services, even beyond lignite the contribution of these services is too small to promote a sustainable regional development in the long term. Although re-cultivated areas are of special interest as many productive agriculture and forestry sites can be included, nature-based solutions and a certain number of undisturbed pristine ecosystems are crucial for improved biodiversity and ES that cannot be directly exploited economically (i.e., as a provisioning service).

With regard to the contribution of this chapter, further research is needed, as the performed assessment only transferred matrix values from another German region, which can merely be a first step. The development of a matrix for the Rhenish mining area, which takes into account the ecosystem conditions and local circumstances in a quantified way, can lead to a valid representation of the spatial potentials. A non-monetary ES valuation can be enabled by comparison of the potential and demand of the ES assessed. Nevertheless, as part of the transformational process of the Rhenish mining area—as well as other comparable regions—the ES concept can be a suitable approach for a sustainable landscape transformation.

To achieve this objective, we propose a long-term strategic process that bases transformation decision on a multi-layered and holistic approach of including ecological, economic, and social aspects in decision making. To this end, important framework conditions should be defined at the outset and translated into utilization budgets, e.g., in the form of budgeted space that is not used for economic purposes. Corresponding land-use plans can thus be derived by defining areas with different land uses such as protected or near-natural state areas, agricultural land, and forests while considering ES provision. Such an approach would provide an overarching level for landscape planning decisions. This would also reduce the danger of fragmented decision-making processes, in which nature-oriented uses are increasingly marginalized in the end. Stakeholder groups should be involved at the strategic level from the very start to allow a higher priority of the ES provision, especially when the value of such services is considered in the related decision-making processes. A participation-oriented approach can thus better ensure the preservation and expansion of ES in the context of transformation processes.