An ecological-economic approach to the valuation of ecosystem services to support biodiversity policy. A case study for nitrogen retention by Mediterranean rivers and lakes

Ecological Indicators 48 (2015) 292–302

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An ecological-economic approach to the valuation of ecosystem services to support biodiversity policy. A case study for nitrogen retention by Mediterranean rivers and lakes Alessandra La Notte a,b,∗ , Camino Liquete c , Bruna Grizzetti c , Joachim Maes c , Benis N. Egoh c,d , Maria Luisa Paracchini c a

University of Torino, Lungo Dora Siena 100 A, 10153 Torino, Italy Department of Agriculture of the Autonomous Province of Trento, Via Trener 3, 38131 Trento, Italy c Joint Research Centre of the European Commission, Via Fermi 2749, 21027 Ispra, VA, Italy d School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa b

a r t i c l e

i n f o

Article history: Received 26 September 2013 Received in revised form 29 July 2014 Accepted 4 August 2014 Keywords: Ecosystem services Economic valuation Conservation policies Water purification Nitrogen retention

a b s t r a c t Several international initiatives have highlighted the need to prove the relevance of ecosystem services in monetary terms in order to make a comprehensive and compelling case for conservation of biodiversity. The different approaches and frameworks used so far have shown that there is no economic or monetary estimate of ecosystems or ecosystem services with absolute validity: any valuation exercise is always context-related and the theoretical rationale behind the applied valuation technique does matter. This study presents an approach for assessing ecosystem services in monetary terms to support conservation policies at the regional and continental scale. First we briefly review the foundation of environmental and ecological economics, second we explore the differences between economic models and the application of valuation techniques, third we try to pick the difference between the mainstream economic valuation approach and the translation of biophysical models’ outcomes in monetary terms. Then we present and discuss a methodology suitable for associating a monetary cost to ecosystem services when the purpose addresses conservation policies. In order to provide a contribution, we show a practical case study on water purification in the northern Mediterranean region. © 2014 Elsevier Ltd. All rights reserved.

1. Introduction Biodiversity underpins most ecosystem processes and its decline affects the delivery of many ecosystem services (Isbell et al., 2011; Cardinale, 2011; Mace et al., 2012). The Millennium Ecosystem Assessment (MEA, 2005) has increased the awareness of the negative consequences of biodiversity loss by emphasizing the role of biodiversity in sustaining livelihood (e.g. local fisheries), economies (e.g. touristic sector) and human wellbeing (e.g. clean air or water). The recent policies at the global and European level have complemented the targets of biodiversity conservation with the arguments of maintaining the delivery of ecosystem services.

∗ Corresponding author at: Department of Agriculture of the Autonomous Province of Trento, Via Trener 3, 38131 Trento, Italy. Tel.: +39 320 6788318. E-mail addresses: [email protected], [email protected] (A. La Notte). http://dx.doi.org/10.1016/j.ecolind.2014.08.006 1470-160X/© 2014 Elsevier Ltd. All rights reserved.

The Convention on Biological Diversity (CBD) calls for the development of strategic plans envisioning that by 2020 ecosystems are resilient and they continue to provide essential services, thereby securing the planet’s variety of life and contributing to human wellbeing. In the European Union (EU), in line with the CBD targets for 2020, the EU Biodiversity Strategy (European Commission, 2011; European Parliament, 2012) emphasizes the link of biodiversity with human well-being through ecosystem services, and seeks to improve the integration of biodiversity conservation in key sectoral policies, including environmental, agriculture, forest and fisheries sectors (COM(2011)244). The European Union is now implementing its updated strategy to mainstream the value of natural capital in diverse sectoral policies, such as the policies on resource efficiency (European Commission, 2011, COM(2011)571 final), environment (COM(2012)710 final), water (COM(2012)673 final) and Green Infrastructure (COM(2012)249). The EU Biodiversity Strategy to 2020 specifically demands that Member States map ecosystem services in their national territories by 2014 and value

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them by 2020. This involves the assessment of the spatial and temporal changes of ecosystem services at the regional scale and their economic valuation (Maes et al., 2012, 2013). Some studies have shown a positive relationship between biodiversity and ecosystem services in different parts of the world (Chan et al., 2006; Egoh et al., 2009; Maes et al., 2012). Although the relationship is complex and currently debated, biodiversity has key roles in ecosystem processes and services (Mace et al., 2012). For example, Cardinale (2011) showed that biodiversity has a positive effect on nitrogen retention, which reduces nitrogen pollution in water bodies. At the same time, biodiversity in freshwater and coastal waters is threatened by high nutrient loadings, which produce hypoxia, fish kills, algal blooms and consequent negative impacts on human and ecosystem health (Diaz et al., 2010; Grizzetti et al., 2011; Sutton et al., 2013). Thus nitrogen retention benefits humans and biodiversity and concurrently is enhanced by biodiversity. Proving the relevance of biodiversity through their contribution to the provision of ecosystem services and valuing them in economic terms can make a comprehensive and compelling case for biodiversity conservation (TEEB, 2010). However, valuing ecosystems or the services they provide is very challenging and can be done using different approaches. Liu et al. (2010) track the milestones in the history of ecosystem service valuation. There is no economic or monetary estimate of ecosystems or ecosystem services with absolute validity: any valuation exercise is always context-related (i.e. the monetary valuation of ecosystem services is always useful as far as its purpose and application are clearly defined). Attributing monetary estimates to ecosystem services, in particular in the context of conservation, is not always without controversy (Farley, 2008; Gowdy et al., 2010; Abson and Termansen, 2011; Spangenberg and Settele, 2010).1 We aim at investigating how to integrate ecological and economic valuation metrics for the production of scientifically rigorous and politically relevant assessments. This paper presents an approach to attribute a monetary value to ecosystem services when the purpose is to support conservation policies related to both biodiversity and ecosystem services at the regional and continental scale. The approach is developed to allow mainstreaming biodiversity conservation into sectoral policies, using the concept of ecosystem services and their monetary valuation as stated above. This research is justified by the pressing requirements for monetary valuation by the new conservation policy strategies at the European scale that require incorporating ecosystem services into policymaking (Maes et al., 2012). The paper is organized in four parts. First it revisits the theoretical assumptions on which our statements are based, that is, the foundations of ecological economics. Secondly, it presents the proposed approach for linking ecosystem services and human well-being in conservation policies. Next, we show its application in a case study: the monetary valuation of the water purification (specifically nitrogen retention) service in the northern Mediterranean region. Finally, the paper discusses the key elements of the analysis undertaken. 2. The foundation of the economic valuation of nature. From environmental to ecological economics A vast literature has been developed presenting arguments for the practical integration of natural and social sciences in the field of ecosystem services, in particular from an economic perspective (e.g. De Groot et al., 2002; Turner et al., 2003; Liu et al., 2010; Seppelt et al., 2011). Before linking ecological models with economic valuation techniques it is important to examine which

1

Some of those critiques are made explicit and discussed in Section 5.

293

economic paradigms are useful for integration. In this section we review the difference between environmental and ecological economics to explain the approach proposed in the paper. Environmental economics was developed in the 19th century to correct market failures in the provision and use of environmental goods and services (Perman et al., 2011). At its core is the theory of externalities and its aim is the optimal allocation and the efficiency in the use of scarce resources. Externalities refer to the cost or benefit of an activity spilling over on a third party such as an ecosystem. In environmental economics, the interaction between economic agents and nature is implicit since the environment is considered as a sub-component of the economy. From a methodological point of view, environmental economics is based on the same concepts and tools as neoclassical economics. Among the main economic concepts are individualism,2 rationality,3 marginalism,4 efficiency criterion5 and general equilibrium models6 extended to environmental issues. The major advantage of environmental economics lies in its analytical rigour and theoretical consistency due to the fact that the only discipline involved is economics even when dealing with environmental issues. The results are thus internally consistent. However, in some cases, environmental economics can be considered precise but not realistic (Bartelmus, 2008) in the sense that a single discipline cannot claim to provide an explanation of the complex dynamics of ecosystems. Eppink and van den Bergh (2007) illustrate that economic models applied to biodiversity conservation show a common trend: the inclusion of model components that address or aim to explain patterns of species diversity declines with increasing complexity of the economic model components. While cost-effectiveness and resource extraction models manage to include biodiversity at some level, macroeconomic growth and general equilibrium models do not. It would be scientifically very challenging to include ecological complexity in economic models without losing the capacity to obtain analytical solutions. Ecological economics is a more recent discipline, finding its origin in the 1980s (Røpke, 2004; Gowdy and Erickson, 2005) and, unlike environmental economics, it is based on natural science. The role of the economic system is inserted in the global ecological system, which is characterized by limited resources and very high complexity. Under the ecological economics paradigm, different scientific disciplines need to interact and the final result is not necessarily expressed in monetary terms but other useful metrics can be used, such Ecological Footprint,7 Habitat Equivalency Analysis,8 Emergy9 or DALY10 (disability adjusted life year). Its major drawback is that different approaches to value ecosystems might not be comparable and consistent. Under this perspective economic activity is the main reason for environmental decline, so the studies are long-term, they support the precautionary principle, and they

2 It emphasizes the moral worth of the individual and promote the exercise of one’s goals and desires. 3 The quality of being consistent with are based on logic. A rational decision is one that is reasoned and also optimal for achieving a goal or solving a problem. 4 The difference made by one extra unit of something. Marginal utility is how much extra utility a person gets from consuming (or doing) an extra unit of something. 5 It refers to the use of resources to maximize the production of goods and services. 6 General equilibrium models explain the behaviour of supply, demand, and prices in a whole economy, in contrast to partial equilibrium models which analyze single markets. 7 References and reports can be found at http://www.footprintnetwork.org/en/ index.php/GFN/. 8 The description of the tool and its application can be found on the NOAA website (http://www.darrp.noaa.gov/economics/papers.html). 9 References and reports can be found at http://www.cep.ees.ufl.edu/emergy/ index.shtml. 10 Definition and statistics can be found on the WHO website (http://www.who.int/ healthinfo/global burden disease/metrics daly/en/).

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DOMAIN

TYPOLOGY OF MODELS (some examples)

OUTPUT

Realm of producon and consumpon acvies

Realm of biodiversity and ecosystem services

LUMP

INPUT-OUTPUT TABLES

ECOpath

SECTORAL MODELS GREENEPIC MACROECONOMIC MODELS

Data in physical and monetary units ready for economic analysis

Data in physical terms

ECONOMIC VALUATION TECHNIQUES

Data in monetary terms

Fig. 1. Economic models (left) and valuation models (right): a visual synthesis set on the basis of policies’ objectives. Example of policy issues related to the realm of production and consumption activities are: resource-saving alternatives to conventional production processes; resource and energy efficiency through eco-taxes, tradable permits and subsidies; and transitional costs of employment shift caused by environmental policies. Example of policy issues related to the realm of biodiversity and ecosystem services are: value of the degradation/loss of ecosystem services as routine basic assessment; monetary quantification of non-market services produced by ecosystems for protection and conservation schemes; and trade-off in monetary terms of different ecosystem services for scenario analysis.

usually call for the reduction of the size of the economy relative to the ecosystem. Among the possible future developments of ecological economics, two paths are identified by van den Berg (2001). The first one requires a strong and intense co-operation between natural and social scientists to build joint theories and models, and the second one aims at focusing on social sciences to provide an alternative paradigm to the neoclassical methodology (Venkatachalam, 2007; Spash, 2008). Although both environmental and ecological economists aim at achieving environmental sustainability, there are essential differences in the way the two disciplines interpret sustainability: the former aims to keep the natural OR human-made capital intact so that economic growth will not decline; the latter aims to lower the pressure on natural systems and holds the precautionary principle in dealing with complexity and uncertainty (Bartelmus, 2008). Ecological economists aim at dematerializing the economy in line with one of the latest EU flagship initiatives about resource efficiency (European Commission, 2011) and advocate for changing behaviour and reducing the impact of human activities (Illge and Schwarze, 2009). The differences between environmental and ecological economists are not clear-cut, there is a continuum of intermediate positions amongst these two schools of thought where most of the researchers act. After reviewing 60 ecological and economic models addressing biodiversity conservation Drechsler et al. (2007) find that economic models form a homogenous group with the following common characteristics: they are general, formulated and solved analytically, with a small number of parameters, and mostly not considering the spatial dimension. Gowdy et al. (2010) express serious doubts on the assumptions of that kind of analytical economic model in dealing with the complexities of the biophysical and social worlds. Ecological models, on the contrary, are less homogenous, but have also some common features like: they tend to be specific,

they are usually formulated analytically but solved numerically, with a large number of parameters and they explicitly take the spatial distribution into account (Drechsler et al., 2007). However, ecological models do not provide results in monetary units but rather in physical units. To translate the biophysical results in monetary terms an economic valuation technique could be used. Fig. 1 shows how the general purpose and structure may differ between economic models (left column) and economic valuations based on ecological models (right column). 3. A framework to value ecosystem services for conservation purposes 3.1. A stronger linkage between ecosystem services and non-market human benefits Different approaches can be used for the valuation of ecosystem services, as summarized in Fig. 2. On the one hand, there are monetary valuation techniques that rely on individual preferences through consumer surplus; they value the demand side because it expresses better what is worth to people (Kumar and Wood, 2010). This approach (e.g. Turner et al., 2003 and references therein) is based on the welfare economics paradigm, in which values are measured in terms of compensating or equivalent variations for individuals, who are assumed rational maximizers of their interests. According to this approach (left column in Fig. 2) the ecosystem service is valued based on revealed or stated preferences (see for instance in the project Aquamoney11 ) using the willingness to pay (WTP) and the basic proxy for the valuation is the

11 Project description and its deliverables can be found at http://www.ivm.vu.nl/ en/projects/Projects/economics/aquamoney/index.asp.

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Fig. 2. Main steps in the valuation of ecosystem services by two different approaches: (1) monetary valuation relying on individual preferences (left column) and (2) valuation technique translating the ecosystem service determined by a biophysical model in monetary terms (right column).

perception of the general public. Ecological/environmental information is usually incorporated into the surveys or the interviews but it is the econometric model describing individual behaviour that quantifies the amount to be valued. The connection of this type of valuation with the actual ecological condition and delivery of ecosystem services can be relatively weak (left arrow in Fig. 2). Thus, individual preferences should preferably be applied to socially defined services, such as the cultural ecosystem services, while more ecologically based services (e.g. regulating services) should have a stronger relationship with the quantification of ecological functions. An alternative possible approach (right column in Fig. 2) is that the quantification of the ecosystem service is first determined by the biophysical model and then translated in monetary terms by using a valuation technique that is consistent with the biophysical model (e.g. the proxy of the valuation could be the cost of not having the ecosystem service any more because the ecosystem is too degraded). The ecological model has to explain the trends of the ecosystem services, their functioning and their change; the purpose of valuation is to translate these results in monetary terms. There could also be intermediate approaches, for example in ARIES12 ecosystem services are modelled as ‘source’, ‘sink’ and ‘beneficiaries’. The strong linkage among the three components offers room for research and analysis on how to develop a valuation that does not completely rely on individual preferences even when considering specific classes of beneficiaries. According to Cowling et al. (2008), an economic valuation aimed at mainstreaming ecosystem services into sustainability policies should be informed by social and biophysical assessments. Building on a tight interdisciplinary collaboration between natural and social scientists, we propose in this study an ecological economics approach to value ecosystem services. Our goal is to develop and analyze an approach for ecosystem services valuation suitable for conservation policies at the regional scale. We argue that, for that purpose, ecological models which base the monetary valuation on biophysical assessments (Fig. 2, right column) are more

12

Ref. http://www.ariesonline.org/about/approach.html.

adequate than economic techniques based on individual preferences (Fig. 2 left column). Moreover, the monetary value of ecosystem services is just “the tip of the iceberg” within the full range of benefits underpinned by biodiversity (Kettunen and ten Brink, 2013). Valuation should only be regarded as a means to communicate information in monetary terms without necessarily losing focus on the goal of conserving biodiversity and associated ecosystem services.

3.2. Valuation steps of the proposed approach Any ecosystem service valuation should be tailored to meet its particular objective: the starting point of any procedure is to clarify the objective. The EU Biodiversity Strategy has the main target of halting biodiversity loss and ecosystem services degradation by 2020. In this context, we apply an integrated approach which combines models drawn from natural sciences with monetary valuation techniques. Then we should identify what to value. We adopt the concept of ecosystem service cascade with a slight difference in assembling the sequence reported in Haines-Young and Potschin (2010) (see Fig. 3). The cascade represents the pathway from ecosystems to humans by differentiating biophysical structures, ecosystem functions, flow of services, social benefits and economic values. In particular, functions are defined as the natural capacity or potential to deliver services; services are what ecosystems do for the people; and benefits are what effectively satisfies human needs and wants (TEEB, 2010). Biodiversity conservation policies try to protect key biophysical structures and processes and the functions they perform to support a stable supply of ecosystem services. Given the purpose of our valuation (support and inform conservation policies), we are interested in attributing a monetary value not only to what people perceive but also to the natural potential or capacity (Fig. 3). Thus, we focus on the natural capacity (function) and on the ecosystem service that is actually being used, but not on the benefit, as it is defined in the cascade. Valuing function and service requires a close link with the biophysical assessment. A temporal assessment of function and service allows evaluating the trends and sustainability of ecosystem service supply.

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Fig. 3. The cascade concept re-adapted for the valuation framework proposed in this study.

There is no risk of double counting as long as it is clear what we are valuing. In fact, as summarized by Fu et al. (2011) one of the most frequent causes of double counting are ambiguous definitions and inconsistent classification of ecosystem services. Valuing the function-service side instead of the service-benefit side is a different point of view with respect to other studies (e.g. Wallace, 2007; Boyd and Banzhaf, 2007; Fisher and Kerry Turner, 2008). Valuing the function-service side may be preferred in large scale assessments for conservation purposes, while at the local scale direct short-term benefits from consumption of products is favoured (Fu et al., 2011). In the following section the basic steps of the procedure are illustrated in a case study. 4. Case study: economic valuation of the water purification service in the northern Mediterranean region We describe a specific case study to illustrate how the proposed approach for economic valuation of ecosystem services can be implemented in practice. For this case study we apply the framework to the ecosystem service ‘water purification’. The case study we present here is drawn from a broader valuation study undertaken over the Mediterranean region whose purpose was to test different spatially explicit valuation approaches to value ecosystem services and specifically water purification (La Notte et al., 2012a, 2012b). In this paper we have a different purpose: we aim at demonstrating how to apply the theoretical principles of the approach into an empirical case study. In addition, we choose a different spatial extent for this application, all European river basins that drain into the Mediterranean Sea, instead of the Mediterranean Bio-geographical region presented in La Notte et al. (2012a). The reasons for choosing a different spatial extent is to show that the methodology proposed here is flexible and can be adapted to the spatial extent relevant to the specific conservation policy, such as Bio-Geographical Regions in the case of the Habitat Directive or River Basin Districts in the case of the Water Framework Directive.

This is possible because in the methodology the quantification of the ecosystem function is based on a spatially explicit model, i.e. values vary in the spatial units. Water purification consists of all processes occurring in soils, sediments and water bodies allowing lowering and/or decomposing pollutants. It concerns pollution mitigation from economic activities and fresh water available for people. The processes occurring before the delivery of the service are complex and this must be kept in mind in order not to oversimplify modelling outcomes. It is not always possible to find a model that describes all the processes involved in the service of water purification. There are models on nitrogen and phosphorus retention, on heavy metals and other chemical and bacterial pollutants. As nitrogen is one of the most abundant pollutants, we choose to focus on indicators related to nitrogen retention as a proxy for water purification. Excessive nutrient loading is indeed a leading cause of water pollution and loss of biodiversity in ecosystems worldwide (Cardinale, 2011; Sutton et al., 2011). Nitrogen applied as fertiliser can easily leach through the soil profile and enter in the aquifer or it can reach surface waters by overland and sub-surface flow. As a consequence, in intensive agricultural regions, excess nitrogen runs in rivers, lakes and coastal waters where it contributes to eutrophication. Similarly, point discharges of urban wastewaters can contribute to water eutrophication. While enhanced nitrogen fixation has undeniable societal benefits, nitrogen is also a powerful environmental pollutant. This intensification of nitrogen release to the environment has resulted in negative effects on human and ecological health (Sutton et al., 2011; Johnson et al., 2010). To assess the nitrogen retention in the Mediterranean Sea basins we used the model GREEN (Geospatial Regression Equation for European Nutrient losses). GREEN is a statistical model developed to estimate nitrogen and phosphorus fluxes to surface water in large river basins. The model was developed and used in European basins with different climatic and nutrient pressure conditions (Grizzetti et al., 2005) and was successfully applied to the

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whole Europe (Grizzetti et al., 2008; Bouraoui et al., 2009a, 2009b; Grizzetti et al., 2012). The advantages and limitations of the modelling approach are discussed in Grizzetti et al., 2008 and Grizzetti et al., 2012. A description of the model GREEN is also provided in Appendix A (Section 1). In this study we used an indicator based on the in-stream nitrogen retention estimated by the model GREEN from 1990 to 2005.13 In-stream nitrogen retention refers to the nitrogen removed from surface waters by biological processes (mainly aquatic plant and microorganism uptake, and denitrification). This represents the actual removal or actual flow of the service (the ‘service’ in Fig. 3). However, the negative effects of nitrogen input on the capacity of systems to remove nitrogen (the ‘function’ in Fig. 3) should also be taken into account. Increasing nitrogen input increases the total amount of nitrogen removed by ecosystems but further increments may impair the capacity of freshwater ecosystems to remove nitrogen. Convincing evidence for streams and rivers is provided by Mulholland et al. (2008), who showed that total biotic uptake and denitrification of stream nitrate increase with stream nitrate concentration but that the efficiency of biotic uptake and denitrification decline as concentration increases. If the goal is supporting sustainability and conservation it is necessary to adopt an indicator that includes the information on the degradation of the capacity of the system to remove nitrogen under increasing nitrogen inputs. To this aim, we developed an indicator, which we called retention capacity, imposing a weighting function to the output of the model (in-stream nitrogen retention) based on the relationship between nitrogen input in the catchment and nitrogen retention. The formulation of this retention capacity indicator is provided in Appendix A (Section 2). After choosing and applying the biophysical model we select the valuation technique that can translate the results of the biophysical assessment in monetary terms. In fact, the choice of the technique and the way it has to be used is strongly related to the biophysical model that is adopted. In our case study we applied the replacement cost technique, in particular we considered the replacement costs of Constructed Wetlands (CW). The rationale that justifies this choice is reported in La Notte et al. (2012a). Here we focus on how this valuation technique links to the biophysical assessment. Because GREEN provides the emissions to the river network that originate from diffuse sources (i.e. mineral fertilizers, manure, atmospheric deposition and scattered dwellings) and from point sources of pollution (urban waste water treatment plants, industries and paved areas), we can differentiate the kind of CW costs according to the type of pressure of nitrogen. Wetlands designed for wastewater treatment are different from those designed for agricultural non-point pollution (Söderqvist, 2002). We decided to apply the costs for surface flow wetland (FWS) to diffuse sources, and the costs for subsurface flow wetland (SSW) to point sources. It is difficult to find a general ‘price list’ for CW, so we collected a number of case studies, especially in the Mediterranean area (the referenced literature is reported in La Notte et al., 2012a, 2012b), and we calculated an average price for the construction, the operation and maintenance of CW. We then created three classes of price (expensive, moderately expensive and not expensive) and within each class we calculated an average price. The annuities related to construction costs are calculated considering a time horizon of 20 years and a 5% interest rate. We then divided the sub-catchments in the Mediterranean region in three groups (high, medium and low) according to the value of the retention capacity indicator, using as thresholds the 25th and 75th percentiles. These three groups of sub-catchments receive accordingly the highest, medium or lowest

13 More technical details on the model design and approach can be found in Appendix A.

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Table 1 Outcomes of the biophysical model in the Mediterranean basin. 1990

2005

Nitrogen input (1000 tonnes) Diffuse input Point input

12,220 300

8020 370

Nitrogen retained (1000 tonnes) River retention Basin retention

330 11,340

340 7100

Source: GREEN Model

monetary value from the classes of price described above. The principle is to attribute higher value (i.e. the most expensive costs) to the sub-catchments that have a higher retention capacity and thus are ecologically better performing. We applied the following formula: V = (N × FWS × d) + (N × SSW × p)

(1)

where V is the estimated monetary value per hectare; N is the normalized nitrogen retention capacity; FWS is the cost per hectare of free water system or surface flow constructed wetlands; d is the diffuse input coefficient; SSW cost per hectare of subsurface flow constructed wetlands; p is the point input coefficient; d and p are the ration of respectively the diffuse input and point input to the stream. The value per hectare must then be multiplied by the number of hectares. We only considered estimates calculated for the river course retention and not for the whole basin (i.e. about the 10% of the whole retention, source GREEN). The river retention increased from 1990 to 2005 (Table 1). Differences in the estimated monetary value relative to the river retention are observed between 1900 and 2005 (Table 2) with an increase in the monetary value of the potential capacity of water purification by river bodies (Table 2) of about 29% ((37,120–28,820)/28,820) corresponding to the average of 8300 euro per kilometre. One of the main outcomes of this assessment is the analysis of the value change over time. The green areas in Fig. 4 are those where the retention capacity increased the most between 1990 and 2005, while the brown areas represent a decrease in the retention capacity. It is not only a matter of attributing a monetary value but also of where the change does take place and how big the change is (to use the standard deviation is an effective way to map these elements). This kind of results allows calculating the differential monetary value of ecosystem services in scenario analysis (La Notte et al., 2012b). The aim of such an approach is therefore to assess ecological/environmental aspects (specifically: water purification) and to attribute a monetary value in order to make a non-market service comparable (to be ranked) with other market services using the same measurement unit (money). The attribution of monetary value can follow different paths. In this case study, the final result is a monetary value calculated for each sub-catchment that directly depends on the biophysical model, specifically: • The results will vary when the in-stream nitrogen retention changes and thus the retention capacity indicator changes. • The Euro-value is attributed according to nature of polluting source and is deeply affected by the ratio between diffuse and point sources.

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Table 2 Monetary value of retention capacity in the Mediterranean Basins (mlln D ). Relative values (average D /km)

Absolute values (mllnD )

1990 2005  1990–2005

Current

Constant (y 2000)

Current

1790 2560

2430 3000 570

21,360 44,000

Constant (y 2000) 28,820 37,120 8300

Fig. 4. Changes in the value of the retention capacity of water bodies between the years 1990 and 2005 (D constant year 2000).

5. Discussion and conclusions In this research work we state the importance of distinguishing between economic valuation and ‘translation in monetary terms’ and we discuss what is the best way to undertake the latter for conservation policies at the regional scale. Some researchers criticizing the economic valuation of ecosystem services propose alternative tools to monetization.14 Although we agree with most of their arguments we believe it is important to make an effort to provide an appropriate valuation in monetary terms because this is the main request by analysts and policy makers (Hughey et al., 2003; TEEB, 2010) and this could help in making a comprehensive and compelling economic case for conservation, of special interest for conservation biologists (e.g. Anton et al., 2010). Monetary valuation based on biophysical models is becoming frequent considering the growing importance and use of modular software tools, such as InVEST, and modelling platforms, such as ARIES that embed the phase of biophysical assessment as the starting point for any kind of analysis based on ecosystem services. The point here is to highlight the importance of understanding the biophysical components before applying valuation techniques or attaching benefit transfer values. In our case study we adopt the replacement cost as an appropriate technical solution based on the output of the biophysical model (i.e. the purification of a relatively low concentration of nutrients in the water that could be replaced by specific human technologies). This approach differs from what happens in a WTP-based model such as Aquamoney, where, for example, the benefits of improvements of the ecological status of Odense River were identified and an Internet survey was conducted to assess the households’ willingness to pay for these benefits (Hasler et al., 2009). As biophysical reference in this case a water quality ladder is used to explain to the interviewed different water quality options and their effects on the conditions for fish and plants, on water visibility.

14 Some example of alternative tools are Multi-Criteria Analysis and Composite Indicators.

We choose the valuation technique depending on the ecological model; we do not filter the outcomes of the model through the demand curve structure, like the mainstream environmental economics approach requires. Below we reflect on some elements that led us to design and follow this approach (versus other economic models based on individual preferences) when the goal is to value ecosystem services for biodiversity conservation. (1) The notion of scarcity: A valuation approach that results in higher value as environmental goods and services are becoming more scarce is less appropriate in this context, because it would indirectly create incentives to increase the scarcity of ecosystems. The same criticism is expressed by Abson and Termansen (2011) and Daily (1997) when they consider the assumption that value should be measured at the margin and they highlight that the marginal value depends on the relative scarcity of the service. (2) The need to value ecosystem services independently from the demand for them: High demand for ecosystem services generates human pressure and can lead to land and sea degradation. This, in turn, may lessen the quality and quantity of ecosystem services provided. Therefore, it is important to value both the actual flow of services used by humans and the capacity of ecosystems to provide the service (i.e. the sustainable flow also referred to as Critical Natural Capital) (Farley, 2008; TEEB, 2010; Villamagna et al., 2013). (3) The background of the stated preference techniques (used in many economic models): When the focus of valuation is the conservation of ecosystems that provide services, people who directly or indirectly express preferences may not fully comprehend the importance of some groups of ecosystem services (especially the regulating and habitat/supporting services). Scientific evidence is mostly lacking when citizens express interest on life’s quantities and qualities (Oreskes, 2004). Thus, the economic analytic structure of stated preferences techniques is consistent with the consumer surplus paradigm, but the results could be misleading and lead to serious underestimates for conservation policies (Spangenberg and Settele, 2010).

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299

Table 3 Summary of the main features to be considered in valuing ecosystem services. Aim of the assessment

What is assessed and valued

Policy making targets

Typology of models implied

Ecosystem consequences

Biophysical structures Ecosystem functions

Conservation policies

Ecological/natural science models

Ecosystem consequences in monetary terms

Ecosystem functions Ecosystem services

Conservation policies Development policies

Ecological/natural science models

Methods that most consistently translate the output of the biophysical model

Economic consequences

Benefits Commodities

Development polices Economic policies

Economic models

Methods that better reflect market behaviour and consumer preferences

(4) The meaning of calculating differential values: Both environmental and ecological approaches do not focus on absolute values but rather use differential values for policy-making purposes. Due to the complexity of ecosystem functions, we advocate for using ecological models to calculate differences in biophysical terms, and then translating those results in monetary terms. Moreover, the issue raised by Gowdy et al. (2010), Abson and Termansen (2011), Spangenberg and Settele (2010), and Farley (2008) about the assumption of marginal analysis that the effect of small changes in one variable can be isolated and evaluated while holding constant everything else (i.e. assuming no connection to other parts of the system) could be somehow solved by using a single biophysical model or a combination of many biophysical models. (5) The reliability of each type of model: There are key features for ecosystem services that ecological models can perform with much more reliability than economic models, namely the spatial configuration (Costanza, 2008), the inclusion of thresholds effects and the non-linearity (Turner et al., 2010). (6) The categorization of ecosystem services: Some of the proposed frameworks of ecosystem services (Balmford et al., 2011, amongst others) identify as feasible for valuation only ecosystem benefits, which refer mostly to natural resources and commodities like food, fresh water or raw materials. The argument behind this choice is to avoid double counting by separating beneficial processes (intermediate services, which may have impacts on many benefits) from the end-benefits (final products/services). Valuing specific functions and services prevents double counting and ensures that the information of many relevant regulating and maintenance services (that could be considered intermediate services) is available for conservation policies (Schröter et al., 2014).

In Table 3 we summarize the concepts and the context of the approach proposed in this paper, according to five main elements of analysis: the ecosystem-economic relationship (column 1), what is assessed and valued (column 2), the targets of the policy making (column 3), the models applied (column 4), and the monetary valuation techniques applied (column 5). The first column of the table, aim of the assessment, refers to the main issue to be valued. Typically, the key question behind economic valuations of ecosystem services and biodiversity is ‘what are the economic consequences of global biodiversity loss?’ However, this is impossible to answer due to (a) our limited knowledge, and (b) the high risk to underestimate and simplify the role of ecosystems. With our approach we perform an ‘assessment in monetary terms’ but not ‘the economic assessment’ (Ref. Fig. 1). Thus, the question becomes rather ‘what is the value of this specific ecosystem service loss in monetary terms?’. In the second column, what is assessed and valued is made explicit through the ecosystem service framework. This framework allows assessing for example the capacity to deliver ecosystem services or the actual flow of ecosystem services, and not only the

Typology of monetary valuation technique

benefits that those services produce (cf. Fig. 3). Still, benefits remain crucial to understand why some ecosystem services are important. In the third column, policy making targets, we identify the policies for which this kind of valuation is suitable. In Europe, the Biodiversity Strategy aims to develop an accurate and conceptually consistent framework for valuing ecosystem services at national and continental level (European Parliament, 2012). But the interest for and relevance of the proposed valuation framework goes beyond conservation policies. Several EU sectoral policies already include ecosystem services and their valuation. For example, in the “2012 Commission’s Blueprint for the future of European waters”, the concept of ecosystem services was identified as one of the pillars of the impact assessment (ref. http://ec.europa.eu/environment/water/blueprint/index en.htm). Similarly, in the new Common Agriculture Policy, restoring and preserving ecosystem services is one of six priorities of the rural development pillar (ref. http://ec.europa.eu/agriculture/ cap-post-2013/index en.htm), and also the Regional and Cohesion policy recognizes that investing in nature is a source of economic development (European Commission, 2011). The typology of models to be applied is linked to the main objective, which in our case is to inform conservation policies. Hence, we recommend to use ecological models (and not only economic models) for the assessment, as already proposed by comprehensive modelling initiatives such as InVEST or ARIES. The role of economics is considered here instrumental to natural science; we do not use economic logic to interpret ecosystem functioning but only to translate what natural science assesses in a language understandable for decision-makers. In such a way, we try to overcome the main problem facing a robust valuation of ecosystem services, namely the gaps in understanding the underpinning science (TEEB, 2010; UK NEA, 2011; Maes et al., 2012). Finally, valuing ecosystem services instead of natural resources and commodities naturally calls for specific typologies of monetary valuation techniques, such as replacement, damage avoidance, or restoration costs (especially for regulating services). These techniques are commonly criticized because they do not represent specifically the demand side (e.g. in Kumar and Wood, 2010; Bateman et al., 2011). As explained throughout this paper, we advocate for estimating the cost of losing ecosystem services in the most realistic way instead of applying an inner consistent, pure economic model. Still, this approach could be less appropriate for some ecosystem services (e.g. recreation) where revealed and stated preferences still remain the best or even sole option available for monetary valuation. Concluding, a crucial step to value ecosystem services (especially regulating and maintenance services) is to base the quantification of the amount to value on the application of biophysical models, and in a second stage to use economic techniques for the translation in monetary terms, based on appropriate proxies as links to the biophysical models as illustrated in the case study. Using the general framework proposed in this paper we provide quantitative and spatially explicit information that (a) reflects the value of ecosystem services for human wellbeing, and (b) can be useful

300

A. La Notte et al. / Ecological Indicators 48 (2015) 292–302

Fig. 1A. Relation between nitrogen input and river retention.

for policy making. This valuation exercise is based on biophysical notions such as the analysis of natural structures and processes or the analysis of ecosystem functions. If we neglect this perspective in the monetary estimation, we may seriously underestimate the value of ecosystem services. Acknowledgement We would like to thank the three anonymous reviewers who provided constructive feedback and helped us to greatly improve the manuscript. Appendix A. A.1. The biophysical model GREEN The model GREEN (Geospatial Regression Equation for European Nutrient losses) contains a spatial description of nutrient sources and physical characteristics influencing the nutrient retention. The area of study is divided into a number of sub-catchments that are connected according to the river network structure. The sub-catchments constitute the spatial unit of analysis. In the application at European scale, a catchment database covering all Europe was developed based on the Arc Hydro model with an average sub-catchment size of 180 km2 (Bouraoui et al., 2009a, 2009b). For each sub-catchment the model considers the input of nutrient diffuse sources and point sources and estimates the nutrient fraction retained during the transport from land to surface water (basin retention) and the nutrient fraction retained in the river segment (river retention). In the case of nitrogen, diffuse sources include mineral fertilizers, manure applications, atmospheric deposition, crop fixation, and scattered dwellings, while point sources consist of industrial and wastewater treatment discharges. In the model the nitrogen retention is computed on annual basis and includes both permanent and temporal removal. Diffuse sources are reduced both by the processes occurring in the land (crop uptake, denitrification, and soil storage), and those occurring in the aquatic system (aquatic plant and microorganism uptake, sedimentation and denitrification), while point sources are considered to reach directly the surface waters and therefore are affected only by the

river retention. For each sub-catchment i the annual nitrogen load estimated at the sub-catchment outlet (Li, ton N/yr) is expressed as following: Li = (DSi × (1 − BRi) + PSi + Ui) × (1 − RRi)

(1A)

where DSi (ton N/yr) is the sum of nitrogen diffuse sources, PSi (ton N/yr) is the sum of nitrogen point sources, Ui (ton N/yr) is the nitrogen load received from upstream sub-catchments, and BRi and RRi (fraction, dimensionless) are the estimated nitrogen basin retention and river retention, respectively. In the model, BRi is estimated as a function of rainfall while RRi depends on the river length. For more details on model parameterisation and calibration see Grizzetti et al. (2008) and Bouraoui et al. (2009a, 2009b). Although simple in its structure the model GREEN is able to provide spatially distributed estimates of nitrogen river and basin retention at large scale. For the application of the economic valuation methods proposed in the present study we specifically considered the following model outputs: The nitrogen retained per sub-catchment by river retention (Nretained river , ton N/yr): Nretained river = Nriver input − Nriver output Nretained river = RRi × (DSi × (1 − BRi) + PSi + Ui)

(2A)

The nitrogen retained per sub-catchment by basin retention (Nretained basin , ton N/yr) Nretained basin = Nbasin input − Nbasin output Nretained basin = BRi × DSi

(3A)

The fraction of nitrogen retained in the river segment of the sub-catchment (RRi, dimentionless) RRi =

RRi =

Nriver input − Nriver output Nriver input (DSi × (1 − BRi) + PSi + Ui) − Li DSi × (1 − BRi) + PSi + Ui

(4A)

A. La Notte et al. / Ecological Indicators 48 (2015) 292–302 Table 1A Regression results. Intercept and slope of the linear regression between nitrogen input and river retention.

Baltic Sea North Sea Celtic Sea and Channels Northern Atlantic Ocean Western Mediterranean Sea Eastern Mediterranean Sea Black Sea Barentz Sea West Norwegian Sea Tuz Salt Lake Prespa Lake

Intercept

Slope

1.8764 1.3432 1.2975 1.4388 2.1864 2.0434 0.5119 1.5208 1.3782 2.2142 1.58108

−0.0034 −0.0004 −0.0009 −0.0019 −0.0019 −0.0003 −0.00008 −0.0365 −0.0291 −0.0055 −0.008

The river or in-stream retention refers to the efficiency to remove nitrogen (expressed as a removal fraction). Fractional nutrient removal is determined by the strength of biological processes relative to hydrological conditions including the residence time and area of contact at the sediment–water interface. In the GREEN model, the in-stream retention is a function of the river length, which is used as a proxy for the residence time. A.2. The indicator for retention capacity In this study we used the nitrogen fluxes estimated by the model GREEN for Europe (Bouraoui et al., 2009a, 2009b) for the years 1990, 2000 and 2005, for the Mediterranean biogeographical region. Based on the outputs of the model GREEN, we developed an indicator to take into account the relationship between the river retention and the nitrogen inputs. Generally, when nitrogen inputs increase, the total amount of nitrogen removed by ecosystems also increases, but further increments may reduce the capacity of the ecosystem to remove nitrogen. To consider this aspect in the analysis, we calculated and indicator which we called retention capacity (N retention capacity ). A regression between nitrogen input (104 kg N km−2 ) and river retention (%) was made for the 10 sea basins into which Europe was divided, using the data per sub-catchment for the year 2000. This resulted in a set of 10 regression parameters, including each time an intercept and a slope. The intercept represents the sea basin averaged in-stream retention (%) if the nitrogen input equals zero. All slopes suggest that river retention decreases if the nitrogen input increases (Table 1A). In Fig. 1A, the river retention is plotted against the nitrogen input in the sub-catchment (sum of point (PSi) and diffuse input (DSi) per km2 ). For all major sea drainage basins, the relationship between nitrogen input in the sub-catchment and river retention is slightly negative. We used the relation found by the regression analysis to impose a weighting function on the in-stream retention estimated by GREEN, assuming a negative effect of nitrogen input on the capacity of freshwater systems to retain nitrogen. The indicator, which we named retention capacity (N retention capacity ), was computed multiplying the river retention (RRi) estimated by the model GREEN by a weighting factor (w) based on the regression coefficients and the nitrogen input, as follow: N

retention capacity

= RRi × w

where: w =1−

−slope × nitrogen input intercept

where slope and intercept are taken from Table 1A. The weighting function w takes value between 0 and 1. Decreasing nitrogen input slightly increases the retention.

We used the indicator retention capacity (N the economic valuation.

301 retention capacity )

for

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