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date: 24 June 2022

Soil Resources, the Delivery of Ecosystem Services and Valuefree

Soil Resources, the Delivery of Ecosystem Services and Valuefree

  • David A. Robinson, David A. RobinsonCentre for Ecology and Hydrology
  • Fiona Seaton, Fiona SeatonCentre for Ecology and Hydrology
  • Katrina Sharps, Katrina SharpsCentre for Ecology and Hydrology
  • Amy Thomas, Amy ThomasCentre for Ecology and Hydrology
  • Francis Parry Roberts, Francis Parry RobertsCentre for Ecology and Hydrology
  • Martine van der Ploeg, Martine van der PloegSoil Physics and Land Management, Wageningen University
  • Laurence Jones, Laurence JonesCentre for Ecology and Hydrology
  • Jannes Stolte, Jannes StolteNorwegian Institute of Bioeconomy Research
  • Maria Puig de la Bellacasa, Maria Puig de la BellacasaSchool of Management, University of Leicester
  • Paula HarrisonPaula HarrisonCentre for Ecology and Hydrology, Lancaster Environment Centre
  •  and Bridget EmmettBridget EmmettCentre for Ecology and Hydrology


Soils provide important functions, which according to the European Commission include: biomass production (e.g., agriculture and forestry); storing, filtering, and transforming nutrients, substances, and water; harboring biodiversity (habitats, species, and genes); forming the physical and cultural environment for humans and their activities; providing raw materials; acting as a carbon pool; and forming an archive of geological and archaeological heritage, all of which support human society and planetary life. The basis of these functions is the soil natural capital, the stocks of soil material. Soil functions feed into a range of ecosystem services which in turn contribute to the United Nations sustainable development goals (SDGs). This overarching framework hides a range of complex, often nonlinear, biophysical interactions with feedbacks and perhaps yet to be discovered tipping points. Moreover, interwoven with this biophysical complexity are the interactions with human society and the socioeconomic system which often drives our attitudes toward, and the management and exploitation of, our environment.

Challenges abound, both social and environmental, in terms of how to feed an increasingly populous and material world, while maintaining some semblance of thriving ecosystems to pass on to future generations. How do we best steward the resources we have, keep them from degradation, and restore them where necessary as soils underpin life? How do we measure and quantify the soil resources we have, how are they changing in time and space, what can we predict about their future use and function? What is the value of soil resources, and how should we express it? This article explores how soil properties and processes underpin ecosystem services, how to measure and model them, and how to identify the wider benefits they provide to society. Furthermore, it considers value frameworks, including caring for our resources.


  • Agriculture and the Environment

Soils and Society

Humanity has had an indelible impact on the earth’s surface, so much so that it has been proposed that the planet has entered a new geological epoch, the Anthropocene (Crutzen, 2002). A population of about 7 billion people that will likely grow to 9.6 billion by 2050 is stressing Earth’s resources. Maintaining the planet in an equitable state for human life is perhaps our greatest challenge. Currently, humans have transformed 38% of the Earth’s ice-free land surface to agriculture, crops, and pasture (Foley et al., 2011). Production agriculture, and the necessity of producing food for a growing population, has had a tremendous impact on our ecosystems and resources, especially through the abstraction of water and by leaving residues. Rockstrom et al. (2009) propose that we need a “safe operating space for humanity with respect to the Earth system,” and that there exist biophysical planetary boundaries (or thresholds) which it is inadvisable to cross if we want to maintain the equable state.

However, consideration of a “safe operating space for humanity” should also take into account the needs of human society (Raworth, 2012). The natural capital and ecosystem services approach is seen as one way of bridging the science/policy divide, improving communication, and working toward an aim of living within sustainable boundaries.

The marriage of ecosystems with the notion of goods and services emerged from the economic and social cultural conditions after the Second World War. Of particular note was the work by Schumacher, which led to the book Small is Beautiful (Schumacher, 1973) and the ecological economic perspectives proposed by the stock-flow, fund-service framework of Georgescu-Roegen (1971). Eventually, researchers felt it necessary to co-opt the language of the dominant ideology of the day in an attempt to increase awareness of the value of natural systems to human society. Westman (1977) suggested that society could make more informed decisions and policy by incorporating the idea that ecosystems offered benefits of social value. The term “ecosystem services” then began to emerge in the early 1980s (Mooney, Ehrlich, & Daily, 1997) “to describe a framework for structuring and synthesizing biophysical understanding of ecosystem processes in terms of human well-being.” Since then, an increasing body of interdisciplinary work has developed that embodies ecology, earth science, economics, and social science, for example, Daly and Farley (2011).

Riding on the back of the mounting wave of both economic globalization and global environmental concern, ecosystem services broke into more widespread awareness with the publication of Daily’s classic text Nature’s Services (Daily, 1997). She offered a broad definition of ecosystem services—including the “conditions and processes” of ecosystems as services (Daily, 1997). She also expressly called the total-use value of ecosystems “infinite,” but argued for the need to assess the “marginal value” of nature (Daily, 1997). While agreeing with Daily on the total welfare value of nature (i.e., infinite), Costanza et al. (1997) identified 17 broad ecosystem services categories and estimated their value at $33 trillion US dollars annually, much to the chagrin of some economists (Spash, 2013). Although not the first, it is probably the most famous attempt to place a financial value on ecosystem services, and has shaped subsequent attitudes to valuation. It must be noted that they regarded their approximation as a minimum estimate, and one which has subsequently been updated to $125 trillion per annum, with a yearly loss of services value from land-use change since 1997 placed at $4.3–$20.2 trillion (Costanza et al., 2014).

A landmark in the uptake of the ecosystem services concept came with the United Nations’ (UN) Millennium Ecosystem Assessment (MEA, 2005). While not an attempt to attribute directly financial value to ecosystem services, the Millennium Ecosystem Assessment (MEA) was, rather, “the first attempt by the scientific community to describe and evaluate, on a global scale, the full range of services people derive from nature” (MEA, 2005). Shockingly, its evaluation concluded that, of the ecosystem services they could reasonably assess, some 60% were in decline (MEA, 2005). With a more comprehensive list than other previous definitions, the MEA attempted to bring some structure and clarity to the concept by devising a four-part classification scheme, so that by the beginning of the 21st century ecosystem services could be meaningfully described as either provisioning, regulating, supporting, or cultural services.

Soils, Challenges, and the Delivery of Ecosystem Services and Their Value

Central to the challenge facing humanity and managing the environment is the fact that the increasing human population is projected to grow to 9 billion by 2050. This, combined with changes in lifestyle, is increasing demand for food and other resources, especially water. Ensuring food security while maintaining the planet in an equable state for a diversity of life is one of our greatest societal challenges. The ecosystem services approach has been heralded as offering a conceptual framework that accounts for the provisioning of goods from nature without neglecting the regulating and cultural services that ecosystems provide, by attempting to link ecosystems with economic value for policymaking. In so doing, it provides a potential way to examine trade-offs and impacts between ecosystem goods and services that may inform policy.

Representing the value of the environment to policymakers and the public is often difficult, something ecosystem service frameworks seek to address by representing how the environment contributes to human well-being. Within this approach, the many benefits humans gain from ecosystems are referred to as ecosystem services (Costanza et al., 1997; MEA, 2005). The stocks within the ecosystem that lead to these services are referred to as natural capital (Costanza et al., 1997). The underlying theory is that as humans see what they gain from ecosystems, they will decide to conserve natural capital, thereby leading to better protection of the natural world. The increasing popularity of ecosystem services is apparent in the conservation literature. A literature search shows that the proportion of papers on ecosystem conservation that include the word “service” or “services” increased from 0.4% in 1984–1985 through 7.7% in 2000–2001 to 28.1% in 2014–2015 (Web of Science search, January 15, 2016). A similar analysis, using Scopus and Google Scholar, found an exponential increase of the number of articles on ecosystem services and an increase in the number of subject areas discussing the concept (Chaudhary, McGregor, Houston, & Chettri, 2015). Governments and institutions are now using the concepts of ecosystem services and natural capital to shape policy frameworks (Chaudhary et al., 2015; Schaefer, Goldman, Bartuska, Sutton-Grier, & Lubchenco, 2015; United-Nations, 2014). However, this method of measuring environmental value still has many shortcomings, which may have long-term impacts on decision-making and the health of the planet (Crompton & Kasser, 2010). And it is not without vehement critics, in both academia (Spash, 2008) and the popular press (Monbiot, 2012).

Soils and Natural Capital

The idea of natural capital can be traced back to the 1830s or earlier (Robinson, Hockley et al., 2013), whereas ecosystem services is more recent. Costanza and Daly (1992) broadly define natural capital as “a stock that yields a flow of valuable goods or services into the future.” In more recent work, Costanza et al. (1997) define it as “the stock of materials or information contained within an ecosystem.” Attempts to define soil natural capital can be found in Palm, Sanchez, Ahamed, and Awiti (2007), who focused on texture, mineralogy, and organic carbon. Robinson, Lebron, and Vereecken (2009) considered soil in a more fundamental sense to be mass, energy, and organization. Both teams considered natural capital to underpin processes and functions for the delivery of ecosystem services.

Soil natural capital may be thought of as a stock, yet it is very much more varied, and resistant to quantification, than that simple word may suggest. Even the relatively well characterized mineral element of soil has considerable uncertainties attached to it, particularly regarding the rate of pedogenesis; some estimates suggest, alarmingly, that rates of erosion are one or two orders of magnitude greater than soil formation in much of the world’s agricultural land (Montgomery, 2007). As if problems of quantifying the physical constituents of soil natural capital were not enough, the fact that its structure must be considered when assessing its condition, and therefore capital value, adds an extra dimension of complexity. Indeed, the size and distribution of the porous voids within a given area of soil are an integral part of its natural capital value. Pore architecture, as much as, and in conjunction with, the elemental aspects of soil, controls the processes and functions, and thus the services and benefits, that arise from the soils beneath our feet (de Jonge, Moldrup, & Schjønning, 2009; Lavelle, 2002). Often thought of as separate spheres, the hydrosphere and pedosphere in fact interpenetrate one another, confined by the porosity of the soil, and it is at this interface, mediated by flows of water, that many of the ecosystem services which we associate with soils originate (Clothier, Green, & Deurer, 2008; Coates et al., 2013).

Soils and Ecosystem Services

Although Daily (1997) was perhaps the first to attempt to classify the ecosystem services of soils, this has been followed by other classifications (Andrews, Karlen, & Cambardella, 2004; Wall, 2004), especially a number for the purposes of agriculture (Swinton, Lupi, Robertson, & Hamilton, 2007). It was Dominati, Patterson, and Mackay (2010) who attempted to pull together a combined soil natural-capital and ecosystem-services framework (Figure 1).

Figure 1. Framework for the Provision of Ecosystem Services from Soil Natural Capital (from Dominati et al., 2010).

This acknowledged the important cycles of soil formation and degradation altering the stock of soil natural capital, which in turn affects the delivery of ecosystem services that fulfill human needs. The proposed framework has served as a benchmark in soil science.

While progress has been made in identifying the ecosystem services that soil delivers or helps deliver (Dominati, Robinson, Marchant, Bristow, & Mackay, 2014; Robinson, Jackson et al., 2013), it has proved challenging to decide where they contribute in overarching ecosystem service typologies. The MEA (2005), the Economics of Ecosystems and Biodiversity, or TEEB (Sukhdev et al., 2010), and the Common International Classification of Ecosystem Services (CICES) (Haines-Young & Potschin, 2012) represent the major ecosystem service classifications. The MEA places soils in the supporting services, whereas the TEEB emphasizes the role of soils in regulating services through erosion prevention and the maintenance of soil fertility. The CICES also focuses on the regulating services provided by soil, with these contributing to a number of groups in the CICES classification, as highlighted in yellow in Figure 2.

Figure 2. The Section, Division, and Group Sections of the CICES Classification of Ecosystem Services. The boxes marked in in the group section represent those with soils contributing (from Haines-Young & Potschin, 2012).

In their report, Haines-Young and Potschin (2012) stated that:

Clarification of the ways soils provide services was a further area identified where the structure of CICES might be looked at: “The system does not currently take account of the services provided by soil very well. [Our] soils scientists identified that the services provided by soil extend beyond the soil formation and composition service identified in the classification.”

They concluded there was a need to reflect better the status of soil and to revise the classification. Figure 3 attempts to synthesize the goods and services identified by Robinson et al. (2013) with the CICES classification.

Figure 3. A focus in on the Group Sections of the CICES Classification of Ecosystem Services (Haines-Young & Potschin, 2012) containing soils, with suggestions for incorporating more soil information in the based on the ecosystem services soils contribute to identified in Robinson et al. (2013).

In addition to groups and classes existing in the classification where soils contribute (yellow), a soil group has been added in provisioning. This highlights that soil resources are widely extracted and used for topsoil, peat, and turf grass and as a building material, for example, for bricks. This analysis also brings out the biological resources extracted from soils like earthworms and microbes used for biomedical resources. Soils play an important role in life cycle maintenance, with an estimated quarter of global biodiversity residing in soils, and in the regulation of pathogens and diseases. Within soil formation it is proposed to focus on soil production and the release of nutrients, as decomposition is dealt with in waste mediation. Soils play a crucial role in climate regulation, both through soil moisture, temperature changes, and carbon storage. With regard to cultural services, in addition to the preservation of heritage, they are also relevant as burial grounds and potentially in terms of bequest value.

One of the challenges regarding the classification of soils is that the direct use of, for example, topsoil or peat is small in comparison to their role as a “means” to underpin the delivery of other ecosystem services, for example, biomass production. This is a concern regarding the ecosystem service approach in that, for reasons of seeking methodological parity with GDP accounting (Boyd & Banzhaf, 2007), the focus has shifted to the delivery of final goods and services. This overlooks the significant potential degradation of soil ecosystems in delivering other services, such as the provisioning of biomass.

United Nations, Sustainable Development Goals (SDGs), and the System of Environmental Economic Accounting (SEEA)

Natural-capital accounting may offer a solution to soil degradation being overlooked due to the dual problem of simply focusing on final goods and services and the fact that soils are often subsumed into larger ecosystem or biome categories when considering ecosystem services (Baveye, Baveye, & Gowdy, 2016). Natural-capital accounting may offer a more complete approach to environmental economic assessment, one which includes ecosystem services but also monitors the state of natural-capital resources. In 2014, the UN launched the System of Environmental Economic Accounts (SEEA), which addresses the fact that GDP, often used as a welfare indicator, does not consider degradation. Perversely, degradation, such as soil erosion, actually stimulates economic activity when remediated, and it is therefore counted as a gain under GDP. The foundation of the SEEA is the identification of seven environmental asset classes (Mineral & energy resources, Timber, Aquatic, Other biological, Water resources, Land cover and Soil). The aim is to assess the extent, volume/mass, and condition of the resources and capture the biophysical and economic flows to correct GDP through satellite accounts. The SEEA, in combination with the ecosystem services approach, has the potential to provide a monitoring and reporting socioeconomic, environmental framework that with the use of biophysical monitoring could provide a global monitoring tool.

If society is to address the United Nations Sustainable Development Goals (SDGs) and attempt to measure their success, it is only through the use of combined social, economic, and environmental monitoring tools that we will be able to make biophysical and economic assessments and measure the trade-offs between development and degradation. We now have an important conceptual framework developing that demonstrates how soils provide functions that deliver ecosystem services which contribute to achieving the sustainable development goals (Figure 4) from (Keesstra, Quinton, van der Putten, Bardgett, & Fresco, 2016).

Figure 4. The Link Between Soil Natural Capital, Soil Functions, Ecosystem Services, and Sustainable Development Goals. Soil threats act to degrade soil natural capital, and this limits the delivery of functions and services. Adapted from Keesstra et al. (2016).

We have modified this figure to include soil natural capital in the central circle, as it is the soil natural capital that supports soil functioning and is vulnerable to degradation. Obst (2015) pointed out that soil remains an underdeveloped component of the SEEA, and there is a job to be done developing a natural-capital framework for soils that describes soil assets. This should acknowledge the important soil cycles, through quantitative assessment of carbon gain and loss, nutrient release, and soil production and erosion, as called for by Amundson et al. (2015). Moreover, it must account for the 11 soil threats, considered in Part 2, that can degrade soils and reduce their capacity to deliver earth-system functions and ecosystem services.

Soil Security

Concurrent to these efforts to link soils and ecosystem services, McBratney, Field, and Koch (2014) argue that soil security must be at the heart of this effort, because soils underpin the delivery of so many services. “Soil security” is defined in McBratney et al. (2014) as maintaining and improving the world’s soil resource to produce food, fiber, and freshwater; contribute to energy and climate sustainability; and maintain biodiversity and the overall protection of the ecosystem. Soils can support the provision of ecosystem goods and services both directly and indirectly, while some soil processes can have a major adverse impact on the delivery of ecosystem goods and services. The ability of soils to function can be threatened by human activity, as identified in The Thematic Strategy for Soil Protection (European Commission, 2006). But something all the ecosystem approaches share is the sense that soils are valuable, and this needs to be articulated.

Valuing Nature or Caring for Our Natural Resources?

The default position of the ecosystem-services approach is to link the environment and economy through monetary valuation. This remains a controversial topic (Baveye et al., 2016; Peterson, Hall, Feldpausch-Parker, & Peterson, 2010). Soils present an interesting case study because they are an economic resource in their own right, as well as supporting major economic activities such as food production. Amundson et al. (2015) argued that agricultural soil systems are one of Earth’s most valuable commodities. They referenced FAOSTAT, which for 2012 estimates that the global production of agricultural products was worth nearly US$3,816 billion. However, agriculture is competing with increasing urban and suburban soil demands. Within soil science, a number of papers have attempted to either value soils and their contribution to the delivery of ecosystem services (Clothier et al., 2008; Dominati et al., 2014; Clothier et al., 2008; Clothier, Green, & Deurer, 2008; Dominati et al., 2014) or reviewed economic valuation of soils (Robinson et al., 2014). With regard to linking to the economy, two approaches appear to be emerging. One deals with the local scale, for example helping farmers make management decisions, often relying on cost-benefit approaches, while at the national scale there is continued development of the SEEA initiative (United Nations, 2014).

Regardless of the valuation approach, ecosystem-service evaluation relies on the first step of biophysical assessment, followed by some form of valuation. With regard to valuation, especially economic, we have yet to determine the exact goals and ways in which it will help us look after and manage soil resources. We know soils are a valuable resource. Life as we know it would not exist without them, but is monetary valuation the best way to express this value?

The Psychology of Value

Due to the way in which human perception functions, it is possible that financial valuation of ecosystems will corrupt their actual value. The relationships between values are not random. They can be more, or less, compatible with each other. Ten distinct value types have been identified across cultures and countries (Schwartz, 2006), within which all values can be placed (Figure 5).

Figure 5. Value Systems: Values are Plotted around a Circle where the Closer They are, the More Compatible They are. Segment titles are in bold and represent a distinct value type. In gray are examples of values for each distinct value type. The layout of values is related to two main axes, the conflict between openness to change and conservation, and also the conflict between prioritizing the physical self and things outside your physicality. Adapted from Schwartz (1992).

This also shows a close correspondence to the structure of individuals’ goals (Grouzet et al., 2005). Correspondence between these main value-types has been found to be consistent across countries, cultures, and economic backgrounds. Individuals differ in the importance they assign to each value (Gollan & Witte, 2014; Grouzet et al., 2005; Schwartz, 2006). Invoking one set of values will suppress opposing values and prime values that correspond to the same value-type (Maio, Pakizeh, Cheung, & Rees, 2009). Understanding how values correspond with each other is thus essential when discussing ecosystem value, as it can have impacts on the behavior of those listening. Therefore, a long-term strategy for environmental protection should appeal to those values which are most likely to engender a positive long-term relationship with nature.

Humans struggle to hold contradictory values in their mind, within their value system, at the same time. Therefore discussion of the environment in financial terms will suppress intrinsic motivation to help the environment. This can be seen in Figure 5, where Wealth, situated in Power, is diametrically opposed to protecting the Environment, situated in Universalism (Schwartz, 1992). Placing a higher emphasis on intrinsic values, situated near Self-transcendence in Figure 5, as opposed to extrinsic values, situated near Physical Self, has been related to a higher willingness to pay to protect the environment (Ku & Zaroff, 2014). However, it must be noted that this study measured self-reported behavior, which only coincides with actual behavior 20% of the time (Kormos & Gifford, 2014). Furthermore, when confronted with actual demands for payment, people are potentially more powerfully primed to think in terms of extrinsic values, which will reduce willingness to pay (Ku & Zaroff, 2014).

In the discussion of the value of the environment, we have to think carefully about what kinds of value we wish to place on it. If we appeal to one value, we also appeal to the values corresponding to the same main distinct value type. This could be powerful in bringing about change. For example, appealing to environmental concerns arguing for car-sharing also increased observed rates of recycling (Evans et al., 2013). However, appealing to a set of values that opposes those already held can reduce the power of the preexisting values. For example, providing monetary incentives to behave in an environmentally friendly way can “crowd out” other motivations to be environmentally friendly, particularly when positive incentives are too small (Rode, Gómez-Baggethun, & Krause, 2014). In order to convey the value of ecosystems, we have to be aware of preexisting values, which may vary by demography, and incorporate tools such as goal setting, social modeling, and prompts (Osbaldiston & Schott, 2012).

Therefore in order to promote the environment we need to appeal to preexisting values, and preferably intrinsic values. But what about soil? Few people have an understanding of the intrinsic value of soil, so it may make sense to appeal to preexisting extrinsic values. However, this may still have undesirable side effects, making people less likely to engage in other pro-environmental behavior and reducing altruism toward other members of society, both present and future. Soil conservation usually involves landowners, who may have different motivations than the students so beloved of psychology experiments. In Sweden, landowners had value structures that tended towards conservation and self-enhancement, and usually engaged in biodiversity conservation projects for altruistic concerns (Johansson, Rahm, & Gyllin, 2013). In order to get people with these types of values involved in conservation, they need to be operating within a context that is supportive of such behavior, making monetary incentives a sensible option (Johansson et al., 2013). However, if the group targeted already has strong intrinsic motivation to help the environment, then building upon that would be more effective.

It will obviously be difficult to target the information provided according to the value system of the beholder. However, the current trend of defaulting to a financial, extrinsic perspective can devalue the environment and remove existing intrinsic motivation to protect the environment. Already we see some undesirable side effects. When the Pope announced that it was a moral obligation to combat climate change, a Republican presidential candidate responded: “I don’t get economic policy from my bishops or my cardinal or my pope” (Teahan, 2015). That may be true, but when did caring for the environment become purely an economic concern?

This was clearly not the intention in the 1970s, with environmentalists discussing ecosystem services who sought a pedagogical tool to help society appreciate the value of ecosystems and highlight the imperative of protecting them (Gómez-Baggethun, De Groot, Lomas, & Montes, 2010). Yet, as the notion of ecosystem services has been inexorably drawn into, and redefined by, the wider societal shift toward neoliberal economics, we have been left with a framework that has commodified ecosystem services and ignores the work done by the supporting services and ecosystem functions that produce them (Peterson et al., 2010).

The value that an individual places on the environment will vary across peoples and cultures, yet the choice to represent the environment solely in financial terms could consistently engender a lack of care for nature. Quantification of value may be important to convince people of the value of the environment, yet too often a quantified value is taken to mean a monetary value. Indeed, the very notion of being able to reduce the pluralistic value of the environment into simple monetary terms without distortion is questionable (Spash, 2008). Alternatives do exist, such as promoting an attitude of care toward the environment, which may foster a more powerful long-lasting relationship when considering conserving and protecting resources such as soil (Puig de la Bellacasa, 2017).

Caring for Soils

In human-environment relations, care has been mostly thought of as delivered by humans to the environment. But humans need everyday care to survive, and it is not difficult to see that much of this care would not be possible without the biophysical world, including living soils. Care is, however, based on very different values from those normally associated with appraising soils’ contribution to human well-being, such as economic worth, natural capital, or provision of services. More than any of these notions, care denotes a necessary relation for the basic survival of living beings. In that sense, thinking about human-environment relations as care has different consequences. Care is a multi-layered notion. It involves work and practice, as in “taking care” of things. It is also affective and emotional, as when we care about something. It has ethical value implying responsibility (Tronto, 1993). It is also an ecological obligation (Puig de la Bellacasa, 2017). Humans and soils are involved in relations that involve all of those dimensions. In a world so affected by human activity, soils cannot live without human care at all these different levels. But the work of care that living soils effectively perform for the web of life is also essential for survival and subsistence. And while the ethical responsibility of soil care is a human affair, its concrete realisation depends on how different soils respond. The care we put into the soils—or the absence of care, neglect—will inevitably affect the capacity of soils to care for all the living beings and processes depending on it.

Linking human-soil relations with care emphasises human interdependency with the environment. Looking at soil value from the perspective of the functions or services which produce human well-being represents an important attempt to change the parameters of a purely economic valuation of natural resources and limited to extraction, production, and consumption. But it has not proved enough to alter the anthropocentric and devastating reduction of nonhuman entities to “resources.” Whether we speak of the services, care, or functions that soils provide in contribution to human well-being, we should consider the possibility of having an obligation to “give back” to soils as much as we receive from them. Relations of care emphasise this condition of liveable interdependency. They invite us to confront the split between nature and culture that posits the human as a consumer of natural resources (Jackson & Palmer, 2015). Emphasizing that we live in an interdependent web of care with biophysical entities of all kinds urges an ethical, emotional, and practical shift toward a more ecocentric relationship with soils.

Biophysical Assessment of Soil Change and the Delivery of Ecosystem Services

Threats to Soil Natural Capital and Function

The protection of soil is of significance for human well-being and social and economic development (Schwilch et al., 2016). Within the 17 UN Sustainable Development Goals (SDG1), soils have a strong relation with SDG 2, 3, 6, 13, and 15 (Bouma & Montanarella, 2016). Keesstra et al. (2016) present steps on how the soil science community can meet these goals (Figure 4). The European Commission (2006) identified eight main threats to soil. These threats were erosion, local and diffuse contamination, loss of organic matter, loss of biodiversity, compaction and other physical soil deterioration, salinization, floods and landslides, and sealing (European Commission, 2006). In some estimates, erosion, organic matter decline, salinization, landslides, and soil contamination alone might cost the EU up to €38 billion annually (European Commission, 2006), and the majority of these costs are borne by society. Recognizing the soil degradation and its transboundary nature, the EC declared in 2006 that for sustainable development, soils need to be protected from degradation. Climatic factors and human actions both threaten soil functioning and natural capital. These threats should not be regarded as distinct. They are interlinked in the sense that threats to soil from human activity can contribute to climate change, and, in turn, climate change causes or intensifies threats to soil.

Soils are under increasing pressure from a wide range of human activities, which undermine their long-term sustainable use. Policy directly or indirectly affects soil threats by enabling and incentivizing, or by prohibiting and limiting, a particular human activity, thereby making activities more or less attractive to land users. Policy regulations, therefore, are a strong instrument in providing opportunities for soil protection. But they can put significant pressure on soils if they are wrongly targeted, and induce overexploitation of resources. From a wider perspective, policy can also affect soil threats by driving changes in land use. The Thematic Strategy for Soil Protection (European Commission, 2006), being the main soil-focused EU instrument, aims to protect soils while using them sustainably, through the prevention of further degradation, the preservation of soil functions, and the restoration of degraded soils (European Commission, 2006; Jones et al., 2012). There is a need to promote the four pillars of the Soil Thematic Strategy. These are (i) more awareness-raising campaigns, (ii) supporting soil research projects, (iii) integration of soil science in policy making, and (iv) improved legislation (European Commission, 2006). Much progress has been made since 2006 on the first three pillars, but no initiatives have been implemented for the legislation at the European scale.

Socioeconomic and cultural drivers directly or indirectly affect soil threats, having a strong link with policy. Feeding an increased population puts pressure on food production through agricultural intensification. Additionally, population growth contributes to the pressures on land resource use through urban growth, mining, and tourism, thereby potentially degrading soils and increasing instances of soil sealing, contamination, and salinization.

Major challenges in understanding and describing the relationship between the various threats to soil and soil functioning are how to quantify the interactions between the various threats and how these interactions in turn affect soil functions. Clarifying these relationships is essential in order to gain a holistic view of the status of threatened soils and the interactions between the different threats and functions of the soil. Table 1 presents an overview of the main challenges threatening soil function. Analysis of the effects of these threats to soil functions is beginning to emerge. By linking the status of soil, in terms of the degree to which it is threatened, with soil functions and ecosystem services, the relationships between those processes driving threats to soil, and thus to the societal benefits derived from soil, may become clearer.

Table 1. The Main Threats to Soil Functions

Soil functions

Main threat


Biomass production (in agriculture and forestry)

Soil erosion by water, soil sealing, salinization, compaction

Gardi, Panagos, Van Liedekerke, Bosco, and De Brogniez, 2015; Li, Pu, Zhu, and Zhang, 2012; Boardman and Poesen, 2007; Håkansson and Reeder, 1994

Storage, filtering, and transformations of nutrients, substances, and water

Soil sealing, contamination, compaction

Etana et al., 2013; Reeves and Baker, 2000

Biodiversity (such as habitats, species, and genes)

Decline in OM and biodiversity loss

Jeffery et al., 2010; Primavesi, 2006

Physical base for construction

Desertification, soil erosion by water, floods and landslides

Morgan, 2006; Van-Camp et al., 2004

Source of raw materials

Floods and landslides

Stankoviansky, Minár, Barka, Bonk, and Trizna, 2010

Acting as carbon pool (store and sink)

Decline in OM and biodiversity

Jeffery et al., 2010; Primavesi, 2006

Archaeological and geological heritage

Soil erosion, floods and landslides, compaction

Camera, Apuani, and Masetti, 2015; Sdao and Simeone, 2007

Monitoring of Soil Natural Capital, State, and Change

In this era of ever-increasing pressure on natural ecosystems and soil, it is essential to monitor ecosystem changes over time. Soil is an integral part of natural ecosystems and is required for biomass production, while also representing a valuable store of carbon and other resources. The need to produce food for the industrial revolution meant that early work on soils focused on inventory and suitability for crop growth, which evolved into soil surveys in many countries in the 20th century. If ecosystems are to be managed for long-term sustainability, an understanding of the long-term response of soil to environmental change is essential. This requires a shift in the way we observe soils, moving from inventory to monitoring of change, as well as experiments to understand the long-term response of soil to change. The need for this is identified in the first report by the UN Food and Agriculture Organisation (FAO), Intergovernmental Technical Panel on Soils (Intergovernmental Technical Panel on Soils, 2015). This proposed that the following four actions are the greatest priorities to stabilize or reverse over exploitation of global soil resources:


Minimize further degradation of soils, and restore the productivity of soils that are already degraded in those regions where people are most vulnerable.


The global stores of soil organic matter (i.e., soil organic carbon (SOC) and soil organisms) should be stabilized or increased.


Act to stabilize or reduce global N and P fertilizer use while simultaneously increasing fertilizer use in regions of nutrient deficiency.


Develop monitoring systems to determine the current state and trend of soil condition. Regional assessments used in the report often predate the 1990s using observations predating the 1980s.

This fourth recommendation requires that we not only consider “state,” but that we must monitor “change.” How else will we know if interventions are effective? In the United Kingdom, the Countryside Survey (CS) was pioneering in this context and has provided evidence of soil change since 1978 (Emmett et al., 2010; Reynolds et al., 2013). Unlike systematic surveys used for inventories, CS is statistically robust, allowing reporting of uncertainty. The robust design has led to the adoption of similar designs at the EU level, for example the Land Use/Land Cover Area Frame Survey (LUCAS) topsoil database, which covers 25 member states of the European Union and provides a basis for soil-related policies (Tóth, Jones, & Montanarella, 2013).

Quantifying the state and change at global scales is challenging, as we simply do not have the data for most countries. Amundson et al. (2015) made an important contribution by attempting to quantify state and change at a global scale for soil carbon, phosphorus, and degradation. They argued that the expansion of urban centers, often termed “soil sealing,” is removing soil from other uses. In Europe, for example, this is now considered to cover on average 9% of the land surface (Scalenghe & Marsan, 2009). Land-use change in the form of creating new cropland is one of the major drivers of imbalances in the soil carbon cycle (Gottschalk et al., 2012), along with accelerated rates of soil erosion (Oldeman, 1994). According to Amundson et al. (2015), phosphorus, critical to plant growth, is unevenly distributed and supplies depend on dwindling geological sources. This global picture of soil degradation is borne out by the national data we do have. Bellamy, Loveland, Bradley, Lark, and Kirk (2005) and Reynolds et al. (2013) both reported a decline in arable-soil carbon in the United Kingdom. Declines were also observed in Belgium (Goidts & van Wesemael, 2007) between 1955 and 2005; in Flanders (Sleutel et al., 2003) between 1989 and 2000, and in arable and pasture systems in the French mountains (Saby et al., 2008) between 1990 and 2004. While we focus mostly on soil organic carbon, it is important to recognize that inorganic carbon is also an important constituent of many soils (Rawlins et al., 2009), and it has also been observed to be in decline, for instance in China (Yang et al., 2012).

The importance of “state and change” monitoring, such as the Countryside Survey (Emmett et al., 2010), is that it shows we cannot have everything, and that we need to make choices. This is made clear by the analysis from Maskell et al. (2013) (Figure 6).

Figure 6. Response Curves of Mean Ecosystem Service Indicators per km Square Across Great Britain, Fitted Using Generalized Additive Models to Ordination Axes Constrained by (a) proportion of intensive land (arable and improved grassland habitats) within each 1 km square from CS field survey data, (b) mean long-term annual average rainfall (1978–2005), and (c) mean soil pH from five random sampling locations in each 1 km square. All x-axes are scaled to the units of each constraining variable. “Butterflies” is abbreviated as “B’flies.” Adapted from Maskell et al. (2013).

The ecosystem service indicators alter, often in a nonlinear way, with proportion of intensive land use (Figure 6a). All but production decline with intensification. Figure 6b and 6c go on to show that changes in moisture inputs, moisture regime, or alteration of soil pH would change the service delivery balance, but at no point do we get everything. In order to make choices, we therefore need decision support, which requires models to help predict the outcomes of interventions.

Modeling: InVEST, LUCI, and ARIES

Soil attributes are a critical component required as input data to model many ecosystem services. Carbon stocks can be directly modeled from soil type using look-up tables and assumptions about soil depth. This is the most commonly applied approach for soil C. However, since soil properties play a role in governing the ecosystem functions which underpin many of the regulating services, soil type is often used as a proxy to model these services on a spatial basis. For example, soil properties dictate how water moves through landscapes (infiltration rates, water storage, runoff), what that water takes with it (soil erosion, nutrient, and pathogen transport into rivers), and the fluxes of the principle greenhouse gases (CO2, N2O, CH4).

There are a wide variety of ecosystem service (ES) modeling tools available, ranging from basic spreadsheets such as the Ecosystem Services Review (Landsberg et al., 2011) to more complex spatial models, which can highlight the key areas within a study site contributing to each service. Three of the main spatially explicit ES modeling tools are InVEST (Sharp, Tallis, Ricketts, & Guerry, 2016); LUCI (Sharps et al., 2017) derived from the Polyscape framework described in (Jackson et al., 2013); and ARIES (Villa et al., 2014). These models can be used to investigate the potential impacts of different management scenarios, for example demonstrating how changes in soil properties can affect service provision, or how soil type mediates the effects of land-cover change. The models can produce maps of service provision and quantitative outputs, including biophysical and (for some services) economic values. The following paragraphs briefly review these models and show how soil information contributes to model outputs.

ARIES—ARtificial Intelligence for Ecosystem Services

ARIES can be more accurately described as a modeling framework which contains a number of ecosystem service modeling applications. A basic principle underlying the ARIES framework is its consideration of multiple aspects of ecosystem service delivery: source, sink, use, and flow. Sources are the aspects of the environment that produce the service, while sinks are aspects of the environment that detract from or reduce the amount of service. Use is the amount of service used by people, and flows are the physical flow-paths or other quantification of how the service reaches the users. The fundamentals of the approach are outlined in Villa et al. (2014), as an extension of ecosystem-services science with a stated aim to renew its focus on beneficiaries and the spatial and temporal dynamics of flows. Numerous individual service models have been developed within ARIES, and it has been applied worldwide in many case studies2 and in multi-service comparisons, for example, Balbi et al. (2015). Many of the original service models use a spatial Bayesian modeling framework. However, other process models can be incorporated by model wrapping, and some, such as the dynamic global vegetation model LPJ-GUESS, which models carbon and water fluxes, have been hard-coded into the software.

Key features of ARIES include the ability to model service flow, flexibility of model development, the ability to incorporate expert knowledge into quantitative models, use in data-poor situations, and representation of uncertainty in model outputs. Service flow is poorly captured in many other ecosystem service models at present, but there is an increasing focus on improving calculation of service flows in ecosystem service assessments (Bagstad, Johnson, Voigt, & Villa, 2013). The flexibility of the modeling approach can be considered both an advantage, due to the ability to write new models or adapt existing models to new applications, and a disadvantage, since there is a certain time investment required to be able to run and use the models. However, there are plans to release an online version with a library of models that could be run with existing (usually global) datasets, but with the capability to load one’s own datasets for bespoke applications. Use of the Bayesian modeling approach confers three advantages. The probabilistic nature of Bayesian approaches means that expert input can be used to generate models for certain services that are otherwise difficult to model, like cultural services (Balbi et al., 2015). It also means that once models have been developed, they can be applied in areas where data is missing or patchy. Lastly, the probabilistic approach allows explicit quantification and mapping of uncertainty in the model outputs, which can be published alongside maps of the service itself, for example, Sharps et al. (2017).

InVEST—Integrated Valuation of Ecosystem Services and Tradeoffs

InVEST is a freely available suite of ecosystem services models, developed by the Natural Capital Project, a partnership between Stanford University and the University of Minnesota, The Nature Conservancy, and the World Wildlife Fund. InVEST combines spatial data on land use and land cover (LULC) patterns with information on the biophysical processes supplying the services and service demand to provide outputs in biophysical or economic terms. The models can be used as stand-alone tools or within ArcGIS, and can be run individually for each service. The spatial resolution of the models is flexible, and models can be run at local, regional, or global scales, depending on available input data. InVEST also has a detailed and comprehensive user guide, with default data available for a number of model inputs (Sharp et al., 2016).

This modeling tool is widely used. Posner, Verutes, Koh, Denu, and Ricketts (2016) reported that 19 different InVEST models were run 43,363 times in 104 countries over a 25-month period (June 2012–June 2014). There are many published studies available, including determining how changes in climate may affect hydrological service delivery in a semi-arid basin in NE Spain (Terrado, Acuña, Ennaanay, Tallis, & Sabater, 2014), investigating how agricultural expansion may impact on biodiversity and carbon storage in Brazil (Chaplin-Kramer et al., 2015), and demonstrating how catchment water quantity and quality vary under a number of land-use change scenarios in China (Zheng et al., 2016).

There are currently 18 InVEST ecosystem services models, plus a number of “helper tools,” available for terrestrial, marine, freshwater, and coastal environments, including examples of cultural, provisioning, supporting, and regulating services. Of these, eight models require information on soil properties (for example, soil erodibility, soil fertility, soil depth, soil carbon, soil type) as a data input (see Table 2). InVEST is an open-source tool and uses Python scripting. Therefore, while the current models can be freely downloaded by users, there is potential for adapting models further for individual use.

Table 2. Soil Data Sets Used in the InVEST Ecosystem Service Model, the Ecosystem Service it Assesses, and the Potential for Future Development

Main soil data it uses

Main ecosystem service assessment that the soil layer contributes to

Potential for development

Carbon density in soil (tonnes/ha) per land use/land cover class.

Carbon storage in soils and biomass (tonnes per grid cell).

Results are as detailed as the land classification used. Classes could be further split by soil type, elevation, or management.

Carbon storage in soil (Mt of CO2 e/ha) per land use class; accumulation rate (Mt of CO2 e/ha-yr), % disturbance and half-life of carbon emitted within soil per land use/land cover class.

Coastal blue carbon: carbon stock, carbon accumulation, carbon emissions, net carbon sequestration (all Mt CO2 e/ha), and net present value (currency/ha).

Currently uses a simplified approach for modeling dynamics of the carbon cycle and is based on a number of assumptions, for example, carbon is assumed to be stored and accumulated linearly through time.

Current global model driven mostly by climate data. Next steps will be to incorporate soil (fertility and depth) and topographic data.

Crop production: crop yield per grid cell, financial analysis (yield, costs, returns, and revenues per crop), nutritional contents (based on values entered by the user for 1 tonne of crop biomass).

Model currently under active development. Further field-level data is required to run a more fine-scale model.

Carbon density in soil (tonnes/ha) per land use/land cover class.

Forest carbon edge effect: carbon storage in soils and biomass (tonnes per grid cell).

This model is an update of the carbon storage model, allowing for the degradation of carbon that occurs in tropical forests due to edge effects.

Nutrient retention due to biochemical degradation in soils (value between 0 and 1); distance (m) after which soil is assumed to retain nutrient at maximum capacity.

Nutrient delivery ratio (nitrogen or phosphorus): total nutrient load in the watershed (kg yr−1); total nutrient export from the water shed (kg yr−1).

Requirement for more accurate export coefficients, from local studies if possible. Sensitivity analyses are recommended to investigate how changes in input data affect final outputs.

Soil erodibility (K) (t ha h ha−1 MJ−1 mm−1); fraction of topsoil particles finer than coarse sand (calibration parameter).

Sediment delivery ratio: total sediment exported to the stream (tonnes per grid cell); sediment retention (tons per watershed).

Currently based on the revised USLE (universal soil loss equation) (Renard, Foster, Weesies, McCool, & Yoder, 1997), which is widely used but has limitations (doesn’t represent all possible erosion processes).

Root restricting layer depth of soil (mm); plant available water content of soil (fraction 0–1).

Water yield: total annual water supply per watershed (m3).

The current model simplifies water consumption (one value per land class).

Soil hydrologic groups (based on hydraulic conductivity and soil depth); Curve number (CN) for each soil group.

Seasonal water yield: outputs are indices for the relative contribution of each grid cell to base flow (occurs during dry weather) and quick flow (present during or just after rain events).

The model does not currently provide quantitative estimates of flow.

LUCI—Land Utilisation and Capability Indicator

The LUCI (Land Utilisation and Capability Indicator) tool was developed to synthesize biophysical data to inform on ecosystem service delivery (Jackson et al., 2013). The model is designed to be able to run with a limited number of data inputs, and has a user-friendly GIS interface. Public release of the model and documentation is planned for 2017. It is designed as a planning tool and is specifically tailored to investigate the impact of farm scale interventions on catchment scale function. To do this, LUCI explicitly tracks the lateral as well as vertical movement of mass (water, sediment, and nutrients) through the landscape at spatial resolutions on the order of meters. Soils data is important in underpinning the outputs from LUCI along with topography, land cover, and climate data. At present soil data must be supplied to match country-specific classifications for England and Wales or New Zealand. There are plans to support global data using the World Reference Base (WRB) soils format. The main ecosystem services modeled by LUCI are agricultural productivity, carbon storage and sequestration, flood risk mitigation, nutrient runoff mitigation, and habitat suitability and connectivity. Of these, the tools for agriculture, carbon, and habitat suitability depend significantly on soil functioning. Table 3 is based on the version using the England and Wales soil-survey data, and shows which ecosystem services the soil data currently contributes to. In New Zealand, the tool has been developed to incorporate influence of soil on N and P exports, and soil hydrological function. These enhancements have not yet been implemented for UK soil (Trodahl, Deslippe, & Jackson, 2016). Trade-offs, impacts, and synergies between individual service provisions can be mapped spatially. The model has been applied at national scale for Wales to inform implementation of agri-environment activities under the Glastir Monitoring and Evaluation Program (Emmett et al., 2014). It can therefore be seen that input data related to soil properties are required for many models, from agricultural production to annual water yield, highlighting the important contribution of soil to a wide variety of ecosystem services.

Table 3. Soil Data Sets Used in the LUCI Ecosystem Service Model, the Ecosystem Service it Assesses, and the Potential for Future Development

Model and soil data it can use

Main soil data it uses

Main ecosystem service assessment that the soil layer contributes to

Potential for development

LUCI, soil survey of England and Wales

Soil water holding characteristics and fertility (by soil association, classified based on expert opinion and literature), slope and aspect

Agricultural productivity potential: category high-low

Bring in effects of slope position (areas accumulating flow more at risk of waterlogging)

Currently based on dominant soil series in association; could add error bounds for other series components


Landcover and soil association combination (classified based on average for that combination from national datasets)

Carbon storage in soils and biomass: kg m−2, category high-low

Include data on slope impacts on soil depth, and estimated effects of different management within the land cover classes. Metamodeling of expected influence of climate change


Landcover and soil association combination (classified based on average for that combination from national data sets)

Carbon sequestration potential: kg m−2, category high-low


Soil type, spatial units for calculation (Simpson’s and Shannon’s indices are calculated based on the chosen level of disaggregation of soil type)

Soil diversity: values for all selected indices in each landscape unit.

Comparison of Models

As the range and complexity of ecosystem-services modeling tools increases, it is important that intercomparisons between models are made, ideally for the same site and services, to help users choose the most suitable tool for their needs. Vigerstol and Aukema (2011) and Bagstad, Johnson, et al. (2013) provide useful overviews of modeling tools, covering model inputs, outputs, and how the models can be applied. The InVEST and ARIES tools were compared for three services (carbon storage, water supply, and scenic viewsheds) in a semi-arid river basin in Arizona (Bagstad, Semmens, & Winthrop, 2013), with similar overall conclusions reached for each service using both tools.

Sharps et al. (2017) also compared modeling tools, running ARIES, LUCI, and InVEST for three services (water supply, carbon storage, and nutrient retention) in a temperate North Wales catchment with a wide variety of land-use types. This study focused on the range of different outputs that each modeling tool can produce per service, and on validating the model outputs against observed data. Using carbon as an example, the mapped outputs from the ARIES, InVEST, and LUCI carbon models can be seen in Figure 7.

Figure 7. Carbon Stocks for the Conwy Catchment, Including Soil and Above-Ground, Below-Ground, and Dead Vegetation for: (a) InVEST, carbon stocks (kg m−2) to 30-cm soil depth; (b) InVEST, carbon stocks (kg m−2) to 1-m soil depth; (c) InVEST, variance associated with carbon stock estimates to 1-m depth (kg m−2); (d) LUCI, carbon stocks (kg m−2) to 30-cm soil depth; (e) LUCI, carbon stocks (kg m−2) to 1-m soil depth; (f) LUCI, carbon sequestration potential (30-cm depth). Carbon concentration: (g) ARIES, expected carbon concentration in topsoil, 15-cm depth; (h) ARIES, uncertainty measured as coefficient of variation (%).

InVEST and LUCI provide directly comparable maps of carbon stock for the study site (Figure 7a and 7d; 7b and 7e). There were some differences between the output maps, both in terms of spatial pattern and in quantities of carbon stocks, particularly for carbon stocks in biomass and soil at a depth of 30 cm. This is thought to be due to differences in the approaches used between the two models, but highlights that not all models will give the same answer, even for a relatively simple service to model, such as carbon. The LUCI carbon model is based on soil type and (aggregated) land-use combinations, whereas the InVEST model uses only land-use data. Despite the differences in spatial distribution of carbon from the two models, the quantitative outputs for InVEST and LUCI (total carbon stocks aggregated to catchment level) were similar and within <10% of each other. LUCI can also provide a map of carbon sequestration potential (Figure 7f), highlighting areas where existing carbon stock is high (red), and therefore with less potential for change, and areas where there is potential for increased carbon if the land-use changed (green). The ARIES model predicted carbon density (g/kg) in the top 15 cm of soil (Figure 7g), rather than carbon stocks. Both InVEST and ARIES can produce maps of uncertainty (Figure 7c and 7h respectively), based on the model inputs used for carbon values per land-use type.

ARIES, InVEST, and LUCI each have different strengths. Customized models can be developed using ARIES, if the user has the technical skills. This tool is also a good option if data are scarce, and it can explicitly model the flow of services such as service use relating to water-based services through the catchment. InVEST can model a wide variety of services, and the manual with default input data is very helpful for new users. This is one of the few tools that currently models some cultural services, and it can also provide economic valuations as an output. LUCI produces traffic-light maps, which allow easy interpretation of model outputs for decision makers. LUCI also has a unique trade-off tool that can demonstrate the potential impact of different scenarios on multiple services, highlighting areas where there may be “win-wins,” with multiple services benefitting, or trade-offs, where one service is improved while another is reduced. There are also some differences in modeling approaches, for example in the scale of model outputs. The InVEST water supply and nutrient-delivery ratio models run at the grid-cell level, with outputs given per watershed, whereas ARIES and LUCI can provide an output for every point in the landscape.

Overall, the choice of modeling tool depends on the question, the available input data, and the scale of outputs required. Sharps et al. (2017) recommend further model comparison studies, running tools for a wide range of services, including cultural services (such as recreation or viewsheds), and also testing models across multiple scales, for example from sub-catchment to sub-continental. There is increasing interest in running ensemble suites of ecosystem service models. This is similar to the approach used in running global circulation models for climate simulations, to capture some aspects of the variability in outputs between models and to start to address issues of uncertainty in model outputs.

Joint Environmental and Socioeconomic Modeling at National to Global Scales

The ecosystem services approach recognizes that we live in a coupled socioeconomic-environmental system. Large-scale ecosystem service models take an integrated, systemic approach to understand better the linkages and feedbacks between different biophysical and human systems. An example of a model attempting this is the Global Unified Meta-model of the BiOsphere (GUMBO). The model divides the Earth’s surface into 11 biomes for assessment. The pedosphere is not dealt with as an explicit module, but it is included in the lithosphere. Predictions for soil formation, carbon and nutrient fluxes, and weathering and erosion processes are included (Boumans et al., 2002). It provides a bold attempt to model the Earth system in an integrated way, incorporating biophysical characteristics of the earth system and socioeconomic aspects of humanity’s activities.

The importance of this integrated approach is further demonstrated by the CLIMSAVE Integrated Assessment Model (IAP) for Europe (Harrison, Dunford, Holman, & Rounsevell, 2016). The IAP integrates models of agriculture, forestry, urban growth, land use, water resources, flooding, and biodiversity within a spatially explicit software environment that operates on 10 × 10 minute spatial grid for the countries of the European Union, plus Norway and Switzerland. It can be used to simulate the impacts of different climate and socioeconomic scenarios on a wide range of sectoral and ecosystem-service output indicators. The linking of the different sectoral models enables analysis of cross-sectoral interactions and assessment of potential trade-offs between ecosystem services. It is designed as an interactive web-based tool that researchers and stakeholders can use to explore and understand cross-sectoral vulnerability to climate and socioeconomic change and how it might be reduced by various adaptation options.


While the ecosystem services approach has proved a stimulus for debate, there are relatively few practical applications that involve soils and valuation that have been fully realized. Developing a fully operational framework is challenging, as it requires biophysical data or models that demonstrate how soils are changing to provide a basis for valuation. With regard to the International System of Environmental Economic Accounts, soils are underdeveloped (Obst, 2015). Recent work to address this has been conducted at the European Union scale (Robinson et al., 2017), setting out the potential of the LUCAS monitoring program to construct and inform central framework accounts. In the United Kingdom, the Office of National Statistics has presented cross-cutting experimental carbon stock accounts (Freeman, 2016), which include soil data from the Countryside Survey monitoring program (Reynolds et al., 2013). At present, these efforts are focused on developing the biophysical accounts, which in themselves are useful for informing policy. The issue these efforts clearly raise is the need for reliable state and change data in addition to modeling (Baveye, 2017; Robinson, 2015). Some of the ecosystem service work at smaller scales looking at costs and benefits has progressed somewhat further.

Aside from the data collection and modeling challenges, valuation is a further challenge: how should the monetary value of soil be determined? A number of examples have been presented that attempt the full linkage and operation for agricultural systems (Porter, Costanza, Sandhu, Sigsgaard, & Wratten, 2009; Sandhu, Wratten, Cullen, & Case, 2008). At a farm level, Dominati used soil and crop modeling combined with valuation techniques including market prices, productivity change, defensive expenditure, replacement cost, and provision cost to demonstrate changes in service delivery over a 35-year period (Dominati, Mackay, Green, & Patterson, 2014). One of the outcomes was a cautionary note on the use of neoclassical economic approaches that are subject to market volatility or where substitutes do not exist. The approach provides another perspective, and one to which many farmers relate, being in monetary terms.

With regard to more policy-focused applications, the important role of soils in underpinning a wide set of services was explored by looking at pressures which affect the quality of soils, and the consequences of altering them. Nitrogen deposition from atmospheric pollution has multiple ecological impacts. These are primarily mediated through changes in soil stocks and processes, as a result of eutrophication and acidification. Changes to soil processes that come about from enhanced atmospheric nitrogen deposition include faster mineralization of organic matter, increased nitrogen availability, greater nitrate leaching, altered stoichiometry, and acidification. These changes cascade through the ecosystem to impact plants and animals, and ultimately people, carrying societal costs and benefits. A UK study looked at the benefits that can come from policies to reduce nitrogen pollution over the period 1987–2005 (Jones et al., 2014). However, because soils underpin so many services, there are multiple effects. Jones et al. (2014) found that reducing nitrogen pollution results in a cost to agriculture and other services which benefit from “free” nutrient inputs to soil. These costs amounted to £4.4m from reduced livestock production, £21.0m from reduced CO2 sequestration, and £1.8m from reduced timber production. However, there were also major benefits to other services: £87.7m due to increased appreciation of biodiversity, £5.3m due to reduced N2O emissions, and £0.03m from improved water quality for recreational fishing. Overall, there was a net benefit of £65.8m. This illustrates the extent to which soil natural capital attributes underpin multiple ecosystem services and provides an example of how both complexity and the altering of soils can have far-reaching consequences.

Cross-Cutting, Dealing with Complexity and Outlook

In a recent article in Nature, (Schmidt et al., 2011) wrote:

Soils are now in the ‘front line’ of global environmental change—we need to be able to predict how they will respond to changing climate, vegetation, erosion and pollution so that we can better understand their role in the Earth system and ensure that they continue to provide for humanity and the natural world.

They recognized that although they constitute only a thin layer of material at the Earth’s surface, soils, like many interfaces, play a pivotal role in regulating the flow and transfer of mass and energy between the atmosphere, biosphere, hydrosphere, and lithosphere. Moreover, the structure and organization of soils leave an important imprint on the earth’s surface in terms of how land is used and how ecosystems develop. Soils help regulate Earth’s physical processes, such as water and energy balances, and act as the biogeochemical engine at the heart of many earth-system cycles and processes on which life depends. Some soil processes contribute to the delivery of ecosystem goods and services directly, while others impact the delivery of goods and services. Soils may actually be “used up” through topsoil or peat extraction, or they may serve as a “means” to the delivery of an ecosystem service as with filtration, and subsequently becoming degraded. This section examines how soil processes impact soil and ecosystem function and the production of goods and services of benefit to humanity.

According to FAO, soils provide the following eleven functions: (1) Water purification and soil contaminant reduction, (2) Climate regulation, (3) Nutrient cycling, (4) Habitat for organisms, (5) Flood regulation, (6) Source of pharmaceuticals and genetic resources, (7) Foundation for human infrastructure, (8) Provision of construction materials, (9) Cultural heritage, (10) Provision of food, fibre and fuel, (11) Carbon sequestration.

How well a soil is suited for any of these functions depends on the feedback with the climate and thus location on the globe, and also on its composition. While all soils contain a different mixture of sand, silt, clay, and organic matter, it is the heterogeneity of that mixture, its chemical composition in combination with growing plant roots and the activity of soil organisms, effectively a soil’s structure, that gives rise to the complexity of soil processes. For example, one of the soil’s ecosystem goods and delivery services is the storage and filtering of water. Soils play an essential role in regulating how much water infiltrates the soil, how much will become surface runoff, how much is available for plant growth, and what quantity will flow toward groundwater. Research on the variability of soil moisture crosses a range of scientific fields, such as agriculture; biochemistry; remote sensing; ecology and hydrology, including its control on nitrification rates; satellite radar interferometry; and climate change science (Brake, Hanssen, van der Ploeg, & de Rooij, 2013; Lawrence & Hornberger, 2007; Robinson et al., 2016). When it comes to biophysical interactions in landscapes—those biotic and abiotic processes in a landscape that have an influence on the developments within and evolution of a landscape, including anthropogenic influences—dealing with the complexity of interacting processes demands collaboration between multiple disciplines. Wassen, de Boer, Fleischer, Rebel, and Dekker (2013) have discussed how anthropogenic loading of nitrogen (N) and phosphorus (P) has changed nutrient availability in many ecosystems, leading to shifts in plant productivity between species, and potentially impacting carbon, N, P, and water cycles; the interactions between these are only beginning to be understood.

Another example illustrating the complexity of soil ecosystem function and services is the process of desertification and restoration. Desertification, defined as land degradation in drylands by the UNCCD, is the result of an interplay between resource exploitation, population increase, and environmental change. The occurrence of desertification in itself can be a matter of debate (Kaptué, Prihodko, & Hanan, 2015), but even more is re-greening (either spontaneous or by restoration efforts) in land-atmosphere interactions and possible feedbacks with precipitation (Giannini, Biasutti, & Verstraete, 2008). The effect of adding water to an ecosystem on the regional climate has been practically applied on a large scale in the form of production enhancement by irrigation, yet quantification of its effects are inconclusive. Douglas, Beltrán-Przekurat, Niyogi, Pielke, and Vörösmarty (2009) used RAMS (Regional Atmospheric Modelling System) to simulate the effects of irrigation in India and found that it increased the regional moisture flux, which in turn increased the convective available potential energy. This led to a reduction in surface temperature, modified regional circulation patterns, and led to changes in mesoscale precipitation. The magnitude and direction of the effect of adding water seem to depend on the extent of an area (Im & Eltahir, 2014), the geographic location (Barnston & Schickedanz, 1984; Chase, Pielke, Kittel, Baron, & Stohlgren, 1999; Sen, Bin, & Yuqing, 2004), and the existing weather patterns (Ozdogan, Rodell, Beaudoing, & Toll, 2010). Some of these studies report an increase in precipitation downwind of an irrigated area (Eddy, Stidd, Fowler, & Helvey, 1975), while others just give the direction of the increase in their specific case (Moore & Rojstaczer, 2002). DeAngelis et al. (2010) concluded that the evapotranspiration of irrigated areas contributes to downwind precipitation, with a larger contribution when evapotranspiration rates are higher, Chase et al. (1999) reported that irrigation in the Colorado Plains has an impact on the climate in the foothills of the Rocky Mountains and even influences the mountains themselves, cloud cover and precipitation being substantially affected. Conversely, Sen et al. (2004) and Im and Eltahir (2014) reported both rainfall increases and rainfall decreases in the vicinity of the irrigated areas, which demonstrates the importance of including feedbacks in our models if we want to truly understand ecosystem services.

Notwithstanding the debate surrounding the complexity in soil processes, disciplines involved in environmental research unite in acknowledging spatial structure and heterogeneity of environmental systems (e.g., Schröder & Seppelt, 2006). Much research is focused on quantifying spatial structure and heterogeneity, such as climate variability, urban sprawl, deforestation, and habitat loss (Ahlqvist & Shortridge, 2010). To be able to understand the emerging patterns resulting from spatial structure and heterogeneity, connectivity has been acknowledged as a useful theoretical concept in ecology (Pringle, 2003), biology (Taylor, Fahrig, Henein, & Merriam, 1993), hydrology (Gomi, Sidle, Ueno, Miyata, & Kosugi, 2008), soil science (Vogel, 2000), and geomorphology (Baartman, Masselink, Keesstra, & Temme, 2013; Bracken & Croke, 2007). The key aspect of the connectivity concept is that it can create pathways for feedbacks, which are so often missing in the contemporary context of soil processes.

Traditionally, the center of gravity for many studies on soil processes has been physically, chemically, and biologically related (Vereecken et al., 2016). Studies considering ecosystem services are often focused on production-related or biodiversity indicators, while links to nontraditional areas such as construction or cultural heritage are somewhat limited. For example, a common framework between soil knowledge and urban planning is missing and generally not considered in urban expansions. Many of the world’s global deltas are urbanized, and further expected urbanization (Heilig, 2012) will result in large parts of the landscape being covered in concrete or asphalt. Especially in deltas, such as for example the Netherlands, soil sealing may increase flood risks if rain water cannot infiltrate into the soil, and sewage systems may not be adequate for extreme rainfall events. While flood and drought risks have obvious economic consequences, environmental indicators and socioeconomic indicators are often perceived as unrelated, especially in urbanized areas. It is assumed that implementing nature-based solutions in the rural areas will also reduce risks in the cities. Built-up areas are all but ignored in the water and soil system, yet are an integral part of it. Those most affected by flood events tend to live in urban centers rather than the countryside, which calls for better integration of soil-related research and urban planning. Couplings developed between humans and natural systems (Liu et al., 2007) necessitate a bridge between the question-driven ecology-centered spatial view and the solution-driven society-centered holistic view (van der Ploeg, 2016; Wu, 2006). Hence the better integration of soil research with other disciplines, and demonstrating how soils and their connectivity underpins the delivery of ecosystem services is the growing challenge of soils research.

This article offers an assessment of the current natural capital and ecosystem service approaches. While these have often stood as two separate ways of looking at nature, efforts like the United Nations System of Environmental and Economic Accounts seek to unify them in an operational framework. Soils are the least developed of the natural resources in terms of framework development, and work is needed to correct this. Clearly this needs to include monitoring of “state and change in condition,” as called for by the United Nations World Soil Resources Report in 2015. A monitoring framework in itself is a powerful tool to inform policy, and to date little progress has been made on how to value soils, which is the next step of the accounting approach. While we recognize that valuation is an integral part of the ecosystem services approach, we must take a step back and consider what it means to value soil, and emphasize the need to care for our resources.


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