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Considering Soils in Ecosystem Service Evaluation

Considering Soils in Ecosystem Service Evaluation

Considering in service evaluation

Demands, examples and challenges

Links4Soils – Considering soils in Ecosysetm Service evaluation

Imprint

What this is about? This report provides an overview about existing research and approaches to link soils with ecosystem services with a special focus on the Alps.

Project and funding Links4Soils (ASP399); EU Interreg Alpine Space

WP, Task and Deliverable WPT1 AT1.3 (D.T1.3.1)

Lead University of Innsbruck, Institute of Geography, Innrain 52f, 6020 Innsbruck, Austria

Authors Elisabeth Schaber1, Michele D’amico2, Michele Freppaz2, Csilla Hudek2, Dorothea Palenberg3 Emanuele Pintaldi2, Silvia Stanchi2, Clemens Geitner1

1 University of Innsbruck, 2 University of Turin, 3 blue! advancing european projects GbR How to cite Schaber, E., D’Amico, M., Freppaz, M., Hudek, C., Palenberg, D., Pintaldi, E., Stanchi, S. and Geitner, C. (2019). Considering soils in evaluation – demands, examples and challenges.

Acknowledgements We would like to thank Borut Vrščaj (Agricultural Institute of Slovenia), Andreja Nève Repe (Slovenian Service) and Ludwig Pertl (Municipality of Kaufering) for reviewing the report.

Date October 2019

Summary for policymakers

How can I make my institution or community -resilient and fit for the future? Your aim is good because it will help to improve the environmental performance of your institution, e.g. a municipal/regional authority or community. Furthermore, the integration of environmental aspects will also help you create a robust and future-oriented economic framework for your further actions. A simple way to integrate environmental aspects into your decision-making is called the “ecosystem service approach”. This is based on the fact that the environment offers many services that are strongly needed but not valued economically. Since the mid-1990s, the “ecosystem service approach“ has driven a new way of measuring the value of these services (e.g. purification) and integrating the values into a new method of cost-benefit analysis. Why is so important for performing a sound ecosystem service analysis? Compared to other ecosystem parts, the role of soils is generally less visible and overlooked, but extremely relevant. The ecosystem services provided by soils ensure that we can rely on crucial conditions for the production of and materials, the regulation of the local and global climate, and the water and nutrient cycles. Soils are cross-cutting and influence the provision of almost all ecosystem services. And we should not forget that soils steer the of our . In a nutshell, the ecosystem services provided and supported by soils should be taken into account even if you make decisions that are not directly related to soil. Why is this especially relevant in Alpine areas? In addition to processes by which soils are threatened in non-mountainous regions, the Alpine environment puts additional strains on soils due to the much slower soil development, steep slopes, promoted , harsh environmental conditions, and the disproportionate development of infrastructure and housing in flat areas in valleys. How can I eliminate my knowledge gap regarding soil quickly, in an up-to-date manner, and with information that takes into account my practical challenges? Soils are extremely diverse, develop over time, and are therefore very complex. Scientists and experts are doing their best to grasp and categorize the many soil ecosystem services and to develop a method for assessing them in such a way that the results can be used quickly and are ready for implementation. Due to the fact that soils are still widely underrepresented in , it is recommended to use networks that try to bridge the gap between scientific findings and practical policy implementation in all sectors. Have a look at the expert platform of the Alpine Soil Partnership (www.alpinesoils.eu), which has been created to transform emerging knowledge into usable methods. What are the main barriers for science that need to be resolved in the future? The difficult soil information situation remains the biggest challenge. Although only a handful of soil parameters would enable an evaluation of the contribution of soils to the

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delivery of ecosystem services, even those are often not available or are only at a scale or quality that is not suitable to the evaluation purpose.

Information on the underlying “Links4Soils“ project In Links4Soils we use the concept of soil ecosystem services to communicate the important role of soils in the Alps in general. Through case studies and tailored approaches, we show how important the consideration of soil is by quantifying soil-based ecosystem services. Furthermore, we have established a database of soil metadata in order to promote the inclusion of soil data in ecosystem service evaluations by other experts and stakeholders to promote better soil protection and sustainable in different sectors.

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Abstract

Ecosystem service (ES) concepts have been developed over the past two decades and are today common in both research and decision-making processes. Although the substantial role of soils was discussed already in one of the first publications on this topic, soils are generally underrepresented in ES research, evaluation frameworks, and case studies. This review provides an overview of the existing ES approaches and classification systems and describes in detail to what extent soils are taken into consideration. Special focus is devoted to Alpine regions. We have also elaborated an overview of the available and required soil data in order to properly implement soils into the ES approach. Therefore, we analysed the indicators used in existing studies. The review of the relevant literature clearly revealed that soils are underrepresented within ES assessments. Furthermore, hardly any ES studies including soil information were found in the Alps and only a few from other mountainous areas. We also identified a lack of soil data and metadata specifically for the Alpine regions. A brief overview is presented regarding how those gaps can be closed and what contribution we can make within the remit of the Alpine Space project “Links4Soils”.

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Content

Imprint______0

Summary for policymakers ______1

Abstract ______3

1 Soils in the Alps ______5

2 The ecosystem service concept ______7

3 Soils and ecosystem services – concept development and approaches ______13

3.1 Existing approaches and examples from mountain areas ______13 3.2 Development and recent approaches (worldwide) ______13 3.3 Existing approaches and examples from the Alps ______20

4 Required and desired data ______23

5 Knowledge gaps on soil-based ecosystem services ______27

6 Contribution of the Links4Soils project ______29

References______31

List of tables ______40

List of figures ______40

About the Links4Soils project ______41

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1 Soils in the Alps

On a global scale, mountain soils sustain food production and support the of ca. 900 million people (da Silva 2015: v). About 70 million people, living in the Alpine space area (defined by the EU; it covers the Alps and close-by regions) and thus, receiving water and other directly from the mountain range, depend on Alpine environments and its soils (Price et al 2011; Heimsath 2014). Under ‘Alpine soils’ we understand the entire range of soils from the valleys to the summits that are found in the Alpine space area. These soils provide many and variegated , as they support agricultural and forest production and biodiversity, retain and purify water, provide nutrients for vegetation, serve as carbon storage, contribute to local cooling and function as natural or cultural archives (Alpine Convention 1998). However, mountain soils are also intrinsically fragile and easily degraded by erosion, loss of organic matter, nutrients and , and acidification. Soil degradation is enhanced by climate change, , or excessive agriculture including overgrazing (Geitner et al. 2017). This degradation has a deep impact on mountain , as soil is a limited , which develops very slowly because of cold climate confining both the speed of weathering and biological activity, and morphodynamic processes at slopes (Alewell et al. 2015). Soil can only persist at a given location if erosion is not removing it faster than it is being produced (Heimsath 2014; Alewell et al. 2015). Soils in the Alps are strongly differentiated according to the parent material’s lithology microclimate, topography, surface age, vegetation cover, and use (Jenny l980; Birkeland 1999; FAO 2015; Baruck et al. 2016; Geitner et al. 2017). All these factors influence by different pathways such as weathering and speed of organic matter turnover. In addition, the rugged and abruptly changing topography affects soil evolution in multiple ways, including the redistribution of the soil material along the slopes to the valley floor resulting in new sites for soil development. As mountain soils are developed in a topographically diverse and strongly dynamic , they are not only highly variable, they also react very sensitively in response to environmental changes. The high spatial variability of Alpine soils represents a unique and valuable environmental heritage, as it supports the development of diverse ecosystems (Geitner et al. 2017). is also a relevant issue at the local and global scale as it determines the complexity of ecological and economic functions. However, societal needs, i.e. food, timber, infrastructure, housing, recreation and other developments, put a strain on the resource soil as they cause a strong competition for the remaining available land, which is in the Alps already limited by the topography and natural hazards. Due to the vulnerability of soils, they deserve particular protection including the implementation of practices to reduce degradation processes. Therefore, the Protocol (SCP) of the Alpine Convention serves as a legal basis for the protection of soils in the Alps (Alpine Convention 1998). However, a survey among soil experts revealed achievements but above all

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shortcomings with regard to the implementation of the SCP (Schaber et al. 2019). In order to minimize soil damage and sealing, management practices have to be further improved and soil-oriented land-use planning tools need to be created, enhanced and implemented. Regarding the latter, the ecosystem services (ES) approach usually serves as a support in land-use planning procedures. Yet, soils have received limited attention within the assessment of ES. The Links4Soils project aims to improve protection and strives towards sustainable soil management in the Alps by overcoming those practical deficiencies.

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2 The ecosystem service concept

This chapter presents the most important conceptual publications related to the ecosystem service approach. It will point out the most important developments since the mid-1990s and it is not intended to provide an exhaustive list of all available works.

The currently most used definition of ES is found in a publication of 2005 commissioned by the United Nations, where ES are defined as the “benefits people obtain from ecosystems” (MEA 2005: v). However, the beginnings of the ES concept and terminology are found in earlier publications.

Daily (1997: 3) published the first comprehensive description of services from ecosystems, which “sustain and fulfil life”, referred to as “’s Services”. The intention was to point out the dependence of the on natural ecosystems and to strengthen the position of . Furthermore, it was aimed to supply economically thinking decision makers with the arguments that nature conservation can lead to economic benefits and, on the other hand, the destruction of ecosystems can result in massive economic costs. Until today, these are the main purposes of the ES approach. Constanza et al. (1998) provide the first publication in which ES are monetized on a global scale. The authors are aware of the controversial opinions, uncertainties and difficulties regarding this kind of valuation of ecosystems and its services, but emphasize its benefits for decision making. De Groot et al. (2002) present a conceptual framework for a comprehensive typology and assessment of ecosystem functions and the goods and services they provide. Ecosystem functions are not synonymous to ES and are defined by De Groot et al. (2002) as “the capacity of natural processes and components to provide goods and services that satisfy human needs, directly or indirectly” (De Groot et al. 2002: 394) (cf. Figure 1). According to the authors, ecosystem functions can be valued in an ecological, sociocultural or economical perspective. The main difference between ecosystem functions and services is that functions only account for the provision of needed goods and services whereas ecosystem services cover both the provision and the demand. However, also ecosystem functions belong to the ES approach, as demand aspects are also considered although they are not included in the evaluations. Regardless of the exact definition, the ES approach enables to understand and bridge the human-nature dichotomy, which is also illustrated in Figure 1. It shows how ecosystems and social systems can be connected with ecosystems services and that ES per definition only exists if there is a provision of services on the one side and a societal demand for the respective services on the other side. People must obtain a benefit from the functioning of the ecosystems and they must value those benefits. Depending on the value they attribute a specific service, they would manage the ecosystems in a way that this service is provided more or less, in Figure 1 referred to as pressures on the ecosystem. Furthermore, it shows, how ES can be classified into supporting services, which ensure the functioning of the ecosystem, and final services, which can be subdivided (after MEA 2005) into provisioning, regulating and cultural services. However, Baveye et al. (2016) argue that the term

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“services” reveals the anthropocentric nature of this approach, which should be kept in mind. If the ES approach is used to support decision-making processes, it is usually extended by the concept of trade-offs and synergies, which is comprehensively discussed by Turkelboom et al. (2015). Despite their claim for clarification of the concept, they provide definitions for trade-offs and synergies. Thereby, a trade-off is defined as “a situation where the use of one ES directly decreases the benefits supplied by another” and its antonym, a synergy is “a situation where the use of one ES directly increases the benefits supplied by another service” (Turkelboom et al. 2015: 2).

Due to the high number and variety of ecosystem functions and services, several classification systems and assessment approaches have been developed and are in use worldwide. De Groot et al. (2002) differentiate four classes of ecosystem functions: ‘regulation’, ‘’, ‘production’, and ‘information’. The Millennium Ecosystem Assessment (MEA, alternative abbr.: MA) and The of Ecosystems and Biodiversity (TEEB) are among the most used frameworks to guide users in their work on ES (Adhikari and Hartemink 2016). They both have their own classification system and assessment approach. In the MEA framework, the ES are grouped into four service categories: ‘provisioning’, ‘regulating’, ‘supporting’, and ‘cultural’ (MEA 2005). Even though the MEA has been the most influential framework and many specific classification frameworks are built on it, Helfenstein and Kienast (2014) stated, that it still fails to create and establish a set of ES indicators. With the aim to support decision making in management, Wallace (2007) proposed the use of a clearer distinction between functions, services and benefits as provided by MEA (2005). Constanza (2008) recommended considering multiple classification systems to be able to accomplish different purposes (e.g. ES classified according to their spatial characteristics). As mentioned by La Notte et al. (2017), in the TEEB classification, the distinction between services and benefits is refined and a new ‘habitat services’ group is introduced, containing ‘maintenance of life cycles’ and ‘maintenance of genetic diversity’ (TEEB 2010) (see Table 1 and Table 2).

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Figure 1: The ecosystem service cascade: ecosystem services link ecosystems and biodiversity with human well-being (modified after Haines-Young and Potschin 2009b)

Table 1: Ecosystem functions/services categories proposed by De Groot (2002), MEA (2005), TEEB (2010) and CICES (2013).

De Groot 2002 MEA 2005 TEEB 2010 CICES 2013 Production Provisioning Provisioning Provisioning Habitat Supporting Habitat Regulating and Regulation Regulating Regulating maintenance Information Cultural Cultural Cultural

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Table 2: Considered ecosystem services/functions with categories by different frameworks (Jónsson and Davíðsdóttir 2016: 26).

With regard to methodological issues, Wallace (2007) points out the problem of double- counting if ecosystem processes to achieve the service provision (‘intermediate services’ or ‘means’) and the services itself (‘final services’ or ‘ends’) are put in the same group. Regarding this challenge, positive examples are the US approaches (Final Ecosystem Goods and Services Classification System (FEGS-CS) and the National ecosystem services Classification System (NESCS)), which allow making clear distinctions between intermediate

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and finale services. This is important for the valuation process as it helps to avoid overlapping in the services and allows a more precise estimation (La Notte et al. 2017).

According to La Notte et al. (2017), the use of different classification systems and approaches has led to differences in the evaluation and interpretation of ES. Consequently, the results of decision-making processes depend on the choice of classification systems, which may harms the confidence in ES approaches. In addition, the comparability of ES assessments cannot be assured. The Common International Classification of Ecosystem Services (CICES) was specifically built in order to overcome these challenges and allow the user to understand similarities and differences between the existing systems (Haines-Young and Potschin 2013; OpenNESS 2017). It is an operational system that is built in a hierarchical structure, as shown in Figure 2.

Figure 2: Structure of CICES by the example of provisioning ES (modified from OpenNESS (2017)).

Unlike other classification systems, CICES is dynamic as it is constantly improved and further developed by a strong user base (cf. CICES 2013; CICES 2018). Table 1 compares the different ES or ecosystem function categories that are proposed by De Groot (2002), MEA (2005), TEEB (2010) and CICES (2013). The presented classification systems all lack the provision of indicators to assess the identified ES and fail to adequately address the role of soils.

In , ambitions to develop besides classification also methodologies to assess and map ES were boosted by the Biodiversity Strategy 2020 (European Commission 2011), as it obliges all member states to complete the mapping and assessment of ecosystems and their services (MAES) for their territory until 2020. Different European research projects (e.g. OpenNESS (Operationalization of and Ecosystem Services) and ESMERALDA (Enhancing ecoSysteM sERvices mApping for poLicy and Decision mAking)) (see overview by La Notte et al. 2017) support the aims of the Biodiversity Strategy 2020. Furthermore, several National Ecosystem Assessments (NEAs) were already developed (e.g. UK NEA 2011) or are in the development phase (NEA-DE). An overview of the NEAs in Europe and their development status in 2016 is given by Schröter et al. (2016). To name one example of an

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Alpine country, Albert et al. (2017) provide a proposal for a National Ecosystem Assessment Germany (NEA-DE). At the examples of provision (Grunewald et al. 2016) and (Syrbe et al. 2018), it is shown how the German indicator set can be used to assess and monitor ES as demanded by the Biodiversity Strategy 2020.

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3 Soils and ecosystem services – concept development and approaches

3.1 Existing approaches and examples from mountain areas

Very few studies deal with ES provided by soils in mountain areas. For example, in the review by Grêt-Regamey et al. (2012) on mountain ES, the only soil aspect that is considered is erosion prevention. Nevertheless, the evaluation was not based on soil data but only on land cover types. In fact, soil as a fundamental of the ecosystem component is not or only marginally considered in most studies. For instance, in the ES evaluation of Crouzat et al. (2015), the contribution of soils is limited to carbon storage. Thus, despite the high diversity and high potential of soils to provide a wide amount of services, a general gap exists in soil- based ES studies in mountain areas.

Rather applied studies for the evaluation of changes were conducted in tropical mountain areas in Central America, in particular, in Honduras, Nicaragua and Guatemala (reviewed by Castro et al. 2015). The focus thereby lies on the effects of management practices and not on the evaluation of the soils. It has been positively noticed that local economic growth has been achieved due to reduced soil degradation 20 years after the implementation of soil protection measures such as instead of the traditional slash-and-burn cultivation. Soil erosion rates have decreased by more than half and most indicators have increased, such as soil organic carbon storage and (Castro et al. 2015). A similar development was observed in a semi-arid region, i.e. the high altitude Pamir (Tajikistan), where the implementation of agroforestry has locally increased soil organic carbon content and decreased soil temperature fluctuation and erosion (Nazarmavloev et al. 2015). Calzolari et al. (2016), presented in section 3.1, also assessed the contribution of soils to ES in a mountainous area, the Apennines. Without any claim to completeness, those examples illustrate how soil can be considered within ES approaches in other mountainous areas than the Alps.

3.2 Development and recent approaches (worldwide)

Since the mid-1970s a number of proposals have been published on how to evaluate soils with different frameworks and classifications (e.g. Brümmer 1978; Várallyay 1987, 1989; Blum and Wenzel 1989; FAO 1995; Blum 2005; Barrios 2007; Haygarth and Ritz 2009; Dominati et al. 2010; Robinson et al. 2013; Baveye et al. 2016; Prado et al. 2016). Baveye et al. (2016) state that the multifunctionality of soils has been considered and studied long before the concept of ES arose, namely in the form of soil functions and soil services

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including the monetization of some. According to Baveye et al. (2016), the history of those evaluations reaches back to the 1940s (e.g. Ciriacy-Wantrup 1947).

In general, each soil has specific physical, chemical and biological properties, which enable corresponding soil processes such as , , weathering, mineralisation, or exchange. Depending on the functional context, one process, or the interaction of a set of those processes, are called soil functions. To assess soil functions and elaborate their contribution to the functioning of the ecosystem is one approach to link soil information to ES (Greiner et al. 2017).

Blum and Wenzel (1989) classified soil functions first into different categories, which were further defined in Blum’s more recent works (Blum 2005; Blum et al. 2006): (a) the extraction of raw materials and water, (b) physically supporting buildings and other man- made structures, (c) geogenic and cultural heritage, (d) , buffering, storage, and chemical/biochemical transformations, (e) the preservation of biodiversity or potentially useful genetic material, and (f) the production of . He distinguishes between non- ecological (a-c) and ecological (d-f) functions. According to Blum (2005), these six functions have an impact on the environment, society and . Thus, sustainable soil management can only be reached, if all six functions are guaranteed without risking the soil to be degraded irreversibly. Even though Blum’s classification is relatively incomplete, it is an important base for the classification and discussion of soil functions and therefore it has been a valuable and influential framework for policy making in Europe since the 1990s. The Soil Directive by the Commission of the European Communities (2006) and the associated soil function classification were inspired by the work of Blum (cf. Table 3). However, soil functions actually do not include the societal demand aspect that is part of the definition of ES.

In the literature since the mid-1990s, different terminology is used to describe the effects of soil properties and processes on the functioning of the entire ecosystem and how this can benefit human well-being, e.g. ‘contribution of soils to the provision of ES’ (e.g. Calzolari et al. 2016), ‘soil-based ES’ (e.g. Ziter and Turner 2018), ‘soil ES’ (e.g. Jónsson and Davíðsdóttir 2016), ‘ES provided by soils’ (e.g. Dominati et al. 2010), ‘ES supplied by soils’ (e.g. Daily 1997), and ‘soil services’ (e.g. Baveye et al. 2016). Although they can be interpreted differently, they are mostly used as synonyms, often even within individual publications. Hereinafter we use the term ‘soil-based ES’ unless we adopt the original terminology of the cited authors.

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Table 3: Comparison of identified ES supplied by soils by Daily (1997) and soil functions by Blum (2005), Commission of the European Communities (2006) and BMLFUW (2013).

Daily 1997 Blum 2005 European Commission 2006 BMLFUW 2013

Physically supporting buildings and Basis of existence and habitat for Physical and cultural environment other man-made structures Preservation of biodiversity or for living creatures and Basis of existence and habitat for

potentially useful genetic material gene pools soil organisms

Physical support of Habitat for natural Production of biomass Production of food and biomass communities Renewal of

Retention and delivery of nutrients to plants Function of soil in the mass balance

Regulation of major element cycles Carbon pool

Buffering and moderation of the Function of soil in the water balance hydrological cycle Filtration, buffering, storage, and Disposal of wastes and dead organic Storage, filtering and transformation Medium for degradation, chemical/biochemical matter of compounds compensation and transformation transformations Extraction of raw materials and Source of raw materials water Archive of geological and Archive of natural and cultural Geogenic and cultural heritage archaeological heritage history

Nevertheless, most general ES frameworks poorly elaborate on the role that soils play in providing ES. For instance, no soil information was included in the assessment of Constanza et al. (1998) and De Groot et al. (2002), which consider soils only in the ecosystem functions ‘water supply’, ‘nutrient cycling’, ‘soil retention’, and ‘soil formation’. Despite the explicit declaration of 'soil formation' or 'soil fertility' as key ES by the frequently used classification systems published by MEA (2005) or Haines-Young and Potschin (2009a) (CICES), both fail to provide methods to include soil information into the evaluation as Dominati et al. (2010) criticize. As a pioneer, Daily et al. (1997) on the other hand, dedicate an entire chapter to ES supplied by soils, which they describe as being infinitely valuable. They identify six ES supplied by soils: (a) physical support of plants, (b) renewal of soil fertility, (c) retention and delivery of nutrients to plants, (d) regulation of major element cycles, (e) buffering and moderation of the hydrological cycle, and (f) disposal of wastes and dead organic matter (cf. Table 3). Yet, this publication is rather descriptive and does not hold specific assessment methods.

Although the pioneering work of Daily (1997) dedicated an entire chapter to ES supplied by soils, in following ES publications soils were often neglected. A reason may lie therein that the ES concept was mostly developed by biologists, which traditionally have a different approach to study soils than other disciplines, e.g. agriculture, , geography or .

Another possible explanation for the lack of soil integrations in general frameworks is that it is challenging to adequately quantifying the contribution of soils to the provision of the services as soil functions are interrelated, meaning most functions have an effect on others.

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Furthermore, there is a lack of standardized definitions and operational tools, which can help to understand theoretical frameworks and represent dynamic processes (Prado et al. 2016). According to Greiner et al. (2017) also most case studies, which use one of the introduced frameworks and do include soil information, still fail to assess more than one soil function, whereby the multifunctionality of soils remains inadequately considered. Another obstacle is the unsatisfactory situation regarding soil data availability and accessibility.

On the other hand, in recent times there are numerous research articles dealing with detailed descriptions of soil functions or ES (e.g. Adhikari and Hartemink 2016; Baveye et al. 2016; Madena et al. 2012; Morel et al. 2014; O'sullivan et al. 2015; Prado et al. 2016). Many researchers call for the integration of soil information into the valuation of ES as soils have both direct and indirect impacts on many ES and thus on human well-being. As shown by Bouma et al. (2015) underpin several case studies in Italy and the Netherlands underpin this demand). Greiner at al. (2017) provide the first review that collects the approved methods to quantify soil functions or soil-related ES. Those so-called soil function assessment methods allow revealing the multifunctionality of soils but do not include any aspects regarding the demand by the society.

Table 4: The main ecosystem services derived from several soil functions (Prado et al. 2016: 1024).

Prado et al. (2016) summarized the main ES derived from the several functions performed by soils (Table 4). Each soil function can be derived from soil properties, such as (obtained through profile description), and chemical and physical analytical data (Table 6) (Greiner et al. 2017). In Europe, soil function approaches are applied or planned to be applied in Germany, Austria, the UK, Switzerland, and partly France (Greiner et al. 2017). In Germany and parts of Austria, the development of applicable but scientifically not very

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sophisticated soil function assessment methods was a reaction to the enactment of national or regional soil protection acts at the turn of the century (Tusch et al. 2009). Some authors (Dominati et al. 2010; Robinson et al. 2013; Samarasinghe et al. 2013) refer to soils as natural capital stocks. Constanza and Daly (1992: 38) define natural capital as “stocks of natural assets (e.g. soils, , water bodies) that yield a flow of valuable ecosystem goods or services into the future”. According to Dominati et al. (2010), soil as a natural capital can be described with soil properties, which they subdivide into inherent (e.g. texture) and manageable (e.g. organic matter). Furthermore, they take into consideration external drivers (e.g. climate, land use) as well as degradation (e.g. sealing, erosion) and supporting (e.g. soil biological activity, nutrient cycling) processes. In this concept, the natural capital and respective processes enable the provision of ES, which contribute by definition to the fulfilment of human needs (Dominati et al. 2010) (Figure 3).

Figure 3: Approach from Dominati et al. (2010: 1863) to link soil (natural capital) to ecosystem services and human needs.

Another approach, which is mainly applied in the US and the Netherlands and was introduced by Larson and Pierce (1991) and Doran and Parkin (1994), is the concept of soil quality and (Moebius-Clune et al. 2016; Greiner et al. 2017). Both terms are often used synonymously but according to Moebius-Clune et al. (2016) they can be differentiated as soil quality refers to both inherent and variable soil properties, whereas soil health is only

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determined by variable properties. Kibblewhite et al. (2008) state that soil health has been defined as a characteristic which shows the capacity of soils to support agricultural cultivation practice without losing the capacity to support multiple other ES. Thereby, a set of qualitative and quantitative indicators of soil health can be evaluated to represent the capacity of the soil to support soil functions. According to the approach of Moebius-Clune et al. (2016), which is applied in the US, field-based soil characteristics, as well as analytical values (e.g. presence of , erosion evidence, compaction, organic matter content, roots, friability, ), can be considered as soil health indicators. However, the derived soil health indicators are usually not service- or function-specific. In other words, even though soil functioning is clearly linked to soil health, its effects on the individual soil functions, and consequently on ES, are often not further differentiated (cf. Volchko et al. 2014 and Moebius-Clune et al. 2016). On the other hand, Ferrarini et al. (2017) state that the soil health concept has recently been extended in order to include the ES aspect. An example therefor is provided by Ferrarini et al. (2014), where five soil functions were assessed by means of different sets of soil health indicators.

In general, the indicator-based soil evaluation depends on one (e.g. infiltration capacity as an indicator for runoff regulation) or a combination of several (e.g. water and nutrient availability and biological activity as indicators for biomass production) soil properties. So- called scoring curves can illustrate the relationships between a soil health indicator (e.g. available water capacity, pH) and the soil performance (Figure 4). The process of creating such scoring curves is explained by Wienhold et al. (2009). They stress out, that apart from the underlying processes and data availability, also site-specific aspects (e.g. climate, inherent soil properties) affect the relationship between the soil health indicator and the soil performance. Usually, the calculated values are standardized, i.e. they vary between 0 and 1 or 0 and 100 (e.g. Moebius-Clune et al. 2016; Volchko et al. 2014), with the highest values representing the highest positive influence on a service. Three general types of the scoring curve are possible: “more is better” (increasing values with increasing soil property, indicating good positive correlation between property and service provisioning), “less is better” (decrease values of service provisioning with increasing soil property), mid-point “optimum” range (good effect at intermediate values, while negative effects are usually at higher and lower property values) (Volchko et al. 2014) (see examples in Figure 4). For example, intermediate values of soil pH are optimal for biological activity, and hence, the pH curve is mid-point. A similar trend curve can be traced for soil content because soils poor in clays have a low water storage capacity, while clay-rich soils can suffer from waterlogging and compaction. A summary of possible curves for different soil properties is available in the review by Ferrarini et al. (2017). An overall soil quality index can be generated by taking the mean of all calculated soil health indicators. Whereas Volchko et al. (2014) classify this soil quality index into five classes (from 1 (very good) to 5 (very poor)) in order to describe the soils ability to generally perform soil functions, Moebius-Clune et al. (2016) argue it is more effective to concentrate on the individual soil health indicators and derive management recommendations directly from them.

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Figure 4: Examples for scoring curves of three factors of soil health or soil quality (Volchko et al. 2014: 788) In contrast to soil quality and health, also threats are frequently discussed in context with the functionality of soils. An approach focussing on soil threats, which can be limited or even prevented by sustainable soil management, was introduced by Schwilch et al. (2016). The approach focusses on the impact of soil threats and their prevention or remediation, respectively, on ES.

Based on MEAs definition of ES, Jònson and Daviðsdòttir (2016: 27) define ‘soil ecosystem services’ (soil ES) as “the benefits people derive from soils”. Consequently, they state, that when assessing the economic value of soil ES in a certain location, both site properties (e.g. land use, climate) and soil characteristics (e.g. ) must be described. Furthermore, a stakeholder assessment must be performed to identify the beneficiaries of the services, from local to global scale. Additionally, they claim the area must be analysed with respect to the existing soil ES, and the soil ES that are selected for economic valuation are then quantified in biophysical terms. Thereby, analytical data or proxies are used, which allow deriving an economic value of each service for the specific case study (Jònson and Daviðsdòttir 2016). Attempting to put price tags on soils, was also the focus of the study by Robinson et al. (2014). While proponents highlight the advantages (e.g. revealing environmental costs or costs of inaction) of a monetary assessment, critical voices argue, that our markets, which follow neoclassical ideals, would most likely not underpin a fair and sustainable soil management, not to mention the inaccuracy that comes with the valuation itself or ethical concerns (What is evaluated (soil biological communities)? What has to be paid? Who pays?) (Baveye et al. 2016).

In order to convince decision makers from the added value and reliability of the assessment and mapping of ES, the data must be reliable and used methods must be transparent (Greiner et al. 2017). However, as Jònson and Daviðsdòttir (2016) stressed, a comprehensive and applicable methodology for the valuation and quantification of soil ES is not available. The paper of Calzolari et al. (2016) is one of the very few publications that provide an applicable, indicator-based approach for the assessment and mapping of, as they say, the ‘contribution of soils to ecosystem service delivery’, which they have approved in the case

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study area of the Emilia-Romagna plain in Northern Italy. It is tailored to the data situation in the region and thus not easily transferable. In this study, they collected indicators and algorithms from several publications and together with comparably good soil data availability they were able to assess the contributions of soil to eight ES. The respective ES categories, the underlying soil functions as well as the used indicators and input data are shown in Table 5.

Table 5: Ecosystem services, soil functions, indicators and data used in the assessment of Calzolari et al. (2016: 193).

A collection of ES assessment models is found in the Integrated Valuation of ES and Trade- offs (InVEST) model (Natural Capital Project 2019). It was developed in the US Natural Capital Project and aims at automated and replicable ES calculations. It is described in detail in a handbook by Sharp et al. (2014) and is freely available online. The spatially-explicit working InVest model uses maps as input data and produces maps at output data. The required soil input data depend on both the evaluated service and the respective model. The tool is increasingly used by researchers in order to map ES (e.g. Nelson et al. 2009; Kovacs et al. 2013).

3.3 Existing approaches and examples from the Alps

This section presents the most important studies in the regional context of the Alps, in which soils are – to a varying extent – linked to ES.

Practical approaches, that can be associated with ES as they are aiming for soil function evaluation, though not specifically created to deal with mountain soils, are provided by several soil function assessment guidelines. The publication of Lehmann et al. (2013) – a

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result from the Alpine Space project TUSEC-IP (Landeshauptstadt München 2006) – provides a collection of algorithms that allow quantifying the fulfilment of soil functions. This applicable collection was originally developed for urban soils in the Alps but can be widely transferred to other areas. The review of Greiner et al. (2017) gives an overview of the soil function evaluation situation in some Alpine countries, i.e. Germany, Austria, Switzerland, and France. In Germany, guidelines from several federal states (e.g. Bavaria: Danner et al. (2003)) were published as a consequence of the Federal Soil Protection Act (BodSchG) adopted in 1998. Based on the German guidelines, but adapted to local conditions, the Austrian BMLFUW (2013) published guidelines for the soil function assessment according to Austrian Standards (ÖNORM L 1076) (cf. Table 3). In both countries, the approach is used as an instrument in order to integrate soil-related issues into (BMLFUW 2013; Greiner et al. 2017; Haslmayr et al. 2016). According to Greiner et al. (2017), in Switzerland assessment methods were created to understand the soil suitability for agricultural purposes, the acidity buffering capacity, filtering and buffering of pollutants such as heavy metals. In France, there are plans to consider soil functions for soil protection in the future (Greiner et al. 2017). In the Italian province of Piedmont, a land capability map was produced according to the FAO classification. It considers a broad range of indicators but only refers to the soil’s suitability for agricultural use (IPLA 2010).

Numerous regional case studies could be found. Landeshauptstadt München (2006) provides a collection of concrete examples that show how soil evaluation can contribute to spatial planning in urban areas in the Alps. Geitner et al. (2017) also present some examples showing how soil functions evaluation can contribute to .

Briner et al. (2013) focus on trade-offs between ES that are an issue in land use planning in the Swiss Alps. As the ES that are influencing each other in their study region (central Valais) they identify the provision of food, the conservation of biodiversity, the sequestration of carbon, and the protection against natural hazards. Yet, soils are not satisfactorily considered in this study. For example, only the aboveground biomass is taken to evaluate carbon storage. Pintaldi et al. (2017) qualitatively assess the changes in ES provided by mountain soils due to ski run construction in the European Alps but no studies could be found that deal in depth and quantitatively with linking soil information to ecosystem services. Another example from the Alpine Space area is the study of Ferrarini et al. (2014) in north-east Italy (Brenta river ). They conducted a study, where they assessed five soil functions by means of different sets of soil health indicators and in a second step, calculated a composite soil health index (SHI) based on the soil function evaluations.

With uncertainties related to soil function evaluation deal Greiner et al. (2018) and Gruber et al. (2019). In a Swiss case study area, Greiner et al. (2018) focus on the error propagation resulting from the prediction of soil properties by means of and the calculations of numerous soil function fulfilment levels. They further developed maps which provide the uncertainty-information to end-users. Gruber et al. (2019) calculate soil

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functions for point information and predict soil function fulfilment levels, based on topographic characteristics, for the entire case study area (South Tyrol).

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4 Required and desired data

At present, there are many publications available, that provide evaluation methods of soil functions or services, but very few of them provide direct quantifications as mentioned by Logsdon and Chaubey (2013), Baveye et al. (2016) and Adhikari and Hartemink (2016). Quantification in this context means, the ES are assessed on a continuous scale, whereas a qualitative evaluation would be categorical (nominal or ordinal) and semi-quantitative a mix of both (Tóth 2015). Accordingly, the ES evaluation is based on quantitative (e.g. slope, stoniness, rockiness, clay content, , carbonates, profile depth), qualitative (e.g. drainage class, degree of mineral weathering, risk of soil erosion) or semi-quantitative (e.g. patches of different colours produced by waterlogging, occurrence of cracks at the soil surface or within , estimation of stone content, estimation of soil macroporosity) soil properties (Terribile 2011).

Precise and quantifiable laboratory data are important, e.g. texture, wet aggregate stability, water retention capacity, organic carbon content, soil respiration, pH, soil nutrients (N and P) and exchangeable bases (Ferrarini et al. 2017; Moebius-Clune et al. 2016). But also qualitative soil properties, among those some can be collected by estimation or simple measurements in the field, such as the presence of earthworms, erosion evidence, compaction, stone content, roots, and friability, are required. For some soil functions or soil- based ES, biological indicators are important, such as microbial biomass, basal respiration, microbial metabolic quotient (ratio between biomass and respiration), maturity index, and QBS (biological soil quality) based on microarthropods and other microbial properties.

From those measurable properties can be inferred onto other, less measurable and more complex characteristics, so-called secondary parameters using pedotransfer functions (Greiner et al. 2017; Haslmayr et al. 2016; Bouma 1989) (see Figure 5). For example, texture affects most physical soil properties, as it influences porosity and structural stability. Pore space, in turn, modifies water retention and movement. Moreover, is correlated with cation exchange capacity, so that clay-rich soils usually retain nutrients. As another example, wet aggregate stability allows deriving secondary parameters as it influences how the soil surface reacts to precipitation events, i.e. how it can cause the sealing of pores or create surface crusts. Both processes lead to increased and thus erosion and to a decreased aeration. Wet aggregate stability can also be used as an indicator of biological quality (Amézketa 1999).

The amount and quality of are among the most important parameters influencing the ability of soils to provide ES. Soil organic matter increases the capacity of soils to retain nutrients and water, it promotes aggregate stability, it constitutes one of the most important carbon sinks, it improves nutrient cycling, and it is the most important base for biological activity and soil biodiversity. Soil biodiversity itself is often used as an indicator

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of soil health (Dominati et al. 2010; Schaetzl and Thompson 2016). However, the availability of biodiversity-related data is still very limited (Jefferey 2010).

Figure 5: Basic soil properties and other geoinformation (i.e. site parameters), as well as pedotransfer functions, are major elements within the assessment of soil functions (Greiner et al. 2017: 233)

A review by Greiner et al. (2017) of the studies quantifying and mapping soil-related ES shows that the most used soil properties are soil organic carbon, stone content, texture, clay content, soil type, hydromorphic properties, soil depth, bulk density, and pH. Other soil parameters appear more rarely, such as the C/N ratio, P and N contents, or aggregate stability. In most cases, those parameters are simply not available.

Regarding the assessment of soil functions, the review of Greiner et al. (2017) allowed them to identify a ‘minimum data set’, consisting of only six parameters, i.e. organic carbon, texture ( and clay content), pH, stone contents, bulk density, and hydromorphic properties, which are required to assess basic functions and, thus, services (Table 6).

In addition to soil data, for a number of services, also site-specific information is of relevance, e.g. land use, parameters or meso- and microclimatic characterization (see Figure 5). For many services, a more holistic-view going beyond the analysis of soil profiles and including landscape information is required. This is demonstrated by the case studies of Gruber et al. (2019) and Calzolari et al. (2016) as they include several site-parameters (i.e. slope, land use, land cover mean air temperature in vegetation period, critical , annual rainfall, mean annual evaporation) in their assessment methods (cf. Table 5).

Even though the assessment of most soil functions or soil-based services only requires a handful of parameters, the biggest challenge and reason, why there has been made little progress in soil function or service evaluation during the last years is the lack of even those few parameters in most parts of the world (Baveye et al. 2016; Greiner et al. 2017), including the Alpine regions and especially for non-agricultural areas (Baruck et al. 2016). Furthermore, Baveye et al. (2016) criticize that ES evaluation is a subject to great

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uncertainty, as many of the used input data are not measured, but estimated or modelled e.g. by means of digital soil mapping. Another challenge is the fact, that original soil data are always point-related and have to be transferred to area-related data, which is obviously also fraught with uncertainty (e.g. Gruber et al. 2019; Greiner et al. 2018). For the modelling of soil parameters, a better data quality, also regarding the scale, of spatial data on soil-forming factors, e.g. geology, would help to improve the results (Geitner et al. 2017). Nevertheless, regarding data accessibility, positive developments can be observed, as the online access on soil data has improved over the last years.

Table 6: Required soil data to assess soil functions (Greiner et al. 2017: 232f.).

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Aggravating the situation, some ES (e.g. recharge) depend on additional properties (e.g. preferential flow pathways), controlled by loose material characterisation (still considered as ‘soil’ by experts in other geoscience disciplines) that extend to much greater depths than the few dm normally studied by soil scientists (Baveye et al. 2016).

In order to improve the data situation, it would be very desirable to do more soil sampling including analytical examinations also regarding microbiology, increase modelling efforts to close data gaps, and develop new analytical methods and area covering mapping techniques for soil properties, e.g. or geophysical methods.

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5 Knowledge gaps on soil-based ecosystem services

Although publications in the field of ES research have increased rapidly since the mid-1990s, the ES concept is still relatively young and its extension to soil-based ES is even less common (Adhikari and Hartemink (2016), Dominati et al. (2010)). As Adhikari and Hartemink (2016) underline in a recent review, soils were included in general ES frameworks only by a few works, mainly carried out in Europe. There are a number of potential reasons, including the lack of data, willingness or specific system knowledge (see section 3.1). Most ES research dealt with provisioning and regulating services, and used soil physical and chemical properties as input data for algorithms to quantify soil-based ES. Only limited work was done on cultural and supporting services, probably due to the intrinsic difficulties in quantifying these services provided by soils through easily measurable properties or already existing data. Adhikari and Hartemink (2016) remark that, even if scientists tried to link soils and their properties to ES, the research was mostly qualitative. Among the quantitative approaches, Baveye et al. (2016) found, that only a few attempted to monetise the ES provided by soils.

Only in a few countries in the Alps (e.g. Italy, see Calzolari et al. 2016), a standardized framework to include soils in the provision of ES from a quantitative point of view was proposed. As remarked by Calzolari et al. (2016), some methodological gaps must be solved prior to establishing a codified framework to include soils in ES provision. Those gaps are manifold and range from participation over data availability, significant indicators, reliable pedotransfer functions and evaluation algorithms to sound mapping methods. Also, Andrew et al. (2015), dealing with ES in general without a focus on soils, indicate similar gaps in current approaches. In particular, Andrew et al. (2015) conclude that the use of available quantitative spatial data (including soil data), which help to assess the ecosystem properties, would significantly improve the parameterisation of automated ES models. As a result, the confidence in the ES concepts and methods would be enhanced. Furthermore, validation efforts (i.e. comparing model results with field observations and measurements) would effectively help to achieve this goal.

Another challenge refers to the complexity of soil process, which are not yet incorporated into available models. Actually, some especially complex processes are not even fully understood. Therefore, new methods to model soil processes are much needed (Vereecken et al. 2016, Vogel et al. 2018). When evaluating the contribution of soils to the provision of ES, not only the uncertainties of data but also those of used models have to be considered (Vereecken et al. 2016).

In the global context, the much-promoted sustainable development goals (SDGs) of the United Nations can only be reached, if transdisciplinary and cross-sectoral approaches, which include , are implemented (Bouma and Montanarella 2016 Calzolari et al. 2016). To achieve these objectives, Baveye et al. (2016) strongly suggest awareness-raising

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campaigns on the importance of soils in everyday life and the active involvement of stakeholders in decision-making processes.

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6 Contribution of the Links4Soils project

The project Links4Soils, co-funded by the European Union within the Alpine Space Programme, strives to close parts of the identified knowledge gaps. Thereby, we are creating a collection of the metadata of the existing spatial soil data within the Alpine regions. This aims to make the integration of soil data into ES assessments easier. However, the harmonisation of soil data is not feasible in the foreseeable future.

We further use the ES approach to communicate the crucial contributions of soils to the provision of ES. The communication will reach from awareness-raising among citizen and policy and decision makers to the assessment of soil functions and soil-based ES as a basis of decision-making. In the initial debate on ES within the Links4Soils project, we selected eleven soil-based ES that we want to consider and, if data availability allows, also assessing in accordance with two criteria. First, soil must play the crucial role in the provision of the service in comparison to other parts of the ecosystem, e.g. the vegetation cover, and second, the service must be relevant in the Alps. An exception is ‘recreational services’, as it only fulfils the second criteria. It was included as it is essential in many touristic regions in the Alps including a case study area within Links4Soils, i.e. Aosta valley. Thus, we focus on the following ensemble of services:

• Agricultural biomass production • Forest biomass production • Surface runoff regulation • Water storage • Local climate regulation (‘cooling effect’) • Global climate regulation (carbon cycle) • Water filtration and purification • regulation • Habitat provision (biodiversity) • Cultural and natural archives • Recreational services

As data availability, used soil analytical methods, algorithms, pedotransfer functions or indicators as well as legislation varies among the Alpine countries or even regions, no universal soil-based ES assessment approach can be developed. In order to assure applicability, the approach must be tailored and proved/verified according to the regional/local conditions. Thereby the potential of the regions shall be used if possible by taking up existing regional or national approaches and developed them further. Yet, it shall reflect our common aim to improve sustainable soil management and soil protection in the Alps by means of assessing ES and implementing more sustainable soil management practices. Those practices shall positively affect soil parameters and properties, from which

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soil-based ES can be derived, which in turn serve as an indicator for the quality and effectiveness of the soil management practices of the recent years or decades.

Apart from the methodological contribution the Links4Soils project strives to enhance the cooperation among soil experts in the Alps and even more important, the exchange between different soil-related sectors (e.g. agriculture, forestry, spatial planning, nature protection) and levels (e.g. policymakers, administration, education, science). For this purpose, the Alpine-wide network ‘Alpine Soil Partnership – AlpSP’ is established within the scope of the project.

Apart from the efforts made within the Links4Soils project, further projects and studies focussing the infinite value of soils for the functioning of ecosystems and for human well- being are much needed.

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List of tables

Table 1: Ecosystem functions/services categories proposed by De Groot (2002), MEA (2005), TEEB (2010) and CICES (2013)...... 9 Table 2: Considered ecosystem services/functions with categories by different frameworks...... 10 Table 3: Comparison of identified ES supplied by soils by Daily (1997) and soil functions by Blum (2005), Commission of the European Communities (2006) and BMLFUW (2013)...... 15 Table 4: The main ecosystem services derived from several soil functions ...... 16 Table 5: Ecosystem services, soil functions, indicators and data used in the assessment of Calzolari et al. (2016) ...... 20 Table 6: Required soil data to assess soil functions ...... 25

List of figures

Figure 1: The ecosystem service cascade: ecosystem services link ecosystems and biodiversity with human well-being ...... 9 Figure 2: Structure of CICES by the example of provisioning ES ...... 11 Figure 3: Approach from Dominati et al. (2010: 1863) to link soil (natural capital) to ecosystem services and human needs...... 17 Figure 4: Examples for scoring curves of three factors of soil health or soil quality ...... 19 Figure 5: Basic soil properties and other geoinformation (i.e. site parameters), as well as pedotransfer functions, are major elements within the assessment of soil functions ...... 24

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About the Links4Soils project

Web links Links4Soils results web page: Alpine Soil Platform – www.alpinesoils.eu Links4Soils Interreg Alpine Space project web page: www.alpine-space.eu/projects/links4soils

Links4Soils project partners

Agricultural Institute of Slovenia, SI (project leader) Kmetijski inštitut Slovenije

Slovenian Forest Service, SI Zavod za gozdove Slovenije

Office of the Tyrolean Provincial Government, AT Amt der Tiroler Landesregierung

Climate Alliance Tirol, AT Klimabündnis Tirol

Institute of Geography, University of Innsbruck, AT Institut für Geographie, Universität Innsbruck

University of Turin, Department of Agricultural, Forest and Food Sciences, IT Università degli Studi di Torino, Dipartimento di Scienze Agrarie, Forestali e Alimentari

Autonomous Region of Aosta Valley, IT Regione autonoma Valle d´Aosta

National Research Institute of Science and Technology for the Environment and Agriculture, Grenoble Regional Centre, FR Institut national de recherche en sciences et pour l'environnement et l'agriculture, Grenoble

Municipality of Kaufering, DE Markt Kaufering

Caring for Soils – Where Our Roots Grow 41

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