ICES Journal of
Marine Science ICES Journal of Marine Science (2016), 73(4), 991– 1003. doi:10.1093/icesjms/fsv264
Review article Economic valuation of Baltic marine ecosystem services: blind spots and limited consistency Julian Sagebiel 1,2*, Carmen Schwartz 1, Mounaim Rhozyel 1, Sandra Rajmis 1‡, and Jesko Hirschfeld 1 1
Institute for Ecological Economy Research, Potsdamer Str. 105, 10785 Berlin, Germany Department of Agricultural Economics, Humboldt-Universita¨t zu Berlin, Unter den Linden 6, 10099 Berlin, Germany
2
*Corresponding author. tel: +49 30 88 45 94-29; fax: +49 30 8825439; e-mail:
[email protected] Present address: Julius Ku¨hn-Institute, Federal Research Centre for Cultivated Plants JKI, Stahnsdorfer Damm 81, 14532 Kleinmachnow, Germany.
‡
Sagebiel, J., Schwartz, C., Rhozyel, M., Rajmis, S., and Hirschfeld, J. Economic valuation of Baltic marine ecosystem services: blind spots and limited consistency. – ICES Journal of Marine Science, 73: 991 – 1003. Received 24 May 2015; revised 8 December 2015; accepted 14 December 2015; advance access publication 26 January 2016. Economic valuation of marine ecosystem services in the Baltic Sea region has gained importance, as policy-makers are recognizing their decline and focusing on achieving good environmental status there in terms of, for example, reduced eutrophication. Parallel with this development, several initiatives have been launched, leading to a large number of economic valuation studies. However, current research indicates that neither a common approach to classifying ecosystem services nor a widely accepted methodological framework for assessing their economic value exist yet. This paper seeks to shed light on the current state of the economic valuation of ecosystem services provided by the Baltic Sea through reviewing all currently available empirical studies on the topic. The results indicate that only a few ecosystem services, including recreation and reduction of eutrophication, have been extensively monetarily valued, and still lack cross-study methodological consistency, while many other marine ecosystem services have rarely or never been valued with economic methods. The paper concludes that existing economic valuation studies provide only limited practical guidance for policy-makers intending to improve the environmental status of the Baltic Sea. There is a need for more widely shared agreement on the systematic nature of marine and coastal ecosystem services and especially on a coherent methodological framework for assessing their economic value. Keywords: Baltic Sea, marine planning, meta-study, nutrient abatement costs, stated preference method.
Introduction The Baltic Sea is one of the largest semi-closed brackish waters in the world. It is almost entirely surrounded by land, with limited water exchange taking place, making it sensitive to environmental influences, especially from human activities (HELCOM, 2010). The need for action to maintain and, in some areas, to improve the environmental status of the Baltic Sea is widely recognized. In 1974, the Baltic Marine Environmental Protection Commission (HELCOM) was founded by the riparian states surrounding the sea with the aim of protecting its coastal and maritime ecosystem services, particularly through reduction of eutrophication. In 2007, HELCOM released the Baltic Sea Action Plan, a coordinated effort to re-establish good environmental status by 2021. Analogously, the European Union published the Marine Strategy Framework Directive in 2008 (European Union, 2008), with the aim of achieving good environmental status for all European Seas by # International
2020. Both of these policy documents explicitly mention that countries should use cost–benefit analysis and the ecosystem services approach to identify their particular need for action and appropriate measures to improve Baltic Sea ecosystem services (Matzdorf and Meyer, 2014). HELCOM (2010) developed a classification of marine ecosystem services for the Baltic Sea, based on the Millennium Assessment Report (Millennium Ecosystem Assessment, 2005). However, several authors have proposed alternative classifications (de Groot et al., 2002; Hein et al., 2006; Boyd and Banzhaf, 2007; Wallace, 2007; Fisher and Turner, 2008; Fisher et al., 2009), with some criticizing the lack of a common method for valuing ecosystem services (Fisher et al., 2009; Clifton et al., 2014; Hirschfeld and Sagebiel, 2014). Recent studies have analysed the current state of the economic valuation literature and pointed out gaps in cost–benefit analyses of ecosystem services. Remoundou et al. (2009) reviewed studies valuing marine ecosystem services around the Black and Mediterranean seas,
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992 also assessing their usefulness and the need for further research. Bo¨rger et al. (2014) compared the use of valuation studies in marine spatial planning in the UK and United States, claiming that the United States is clearly taking a pioneering role, especially when it comes to using valuation studies in policy-making. Clifton et al. (2014) reviewed available valuation methods for marine ecosystem services and identified not only high variability but also lack of consistency in outcomes. Bertram and Rehdanz (2013) reviewed the valuation literature on Europe’s seas and discussed current challenges to cost-benefit analysis in the context of the Marine Strategy Framework Directive. In the Baltic Sea context, Bertram et al. (2014) pointed out gaps in valuation of marine ecosystem services and found there are few studies valuing their benefits. In a recent book on the economics of ecosystem services, Nunes et al. (2014) summarized the call of many researchers for a unified classification and valuation framework. In sum, all of these studies have identified limitations in existing concepts of ecosystem service classification and valuation for cost-benefit analysis. This paper aims to complement previous discussions on valuing marine ecosystem services by providing facts and figures regarding the current state of valuation methods and their application to the Baltic Sea region. All available studies that have valued at least one ecosystem service provided by the Baltic Sea between 1995 and 2015 are systematically analyzed with regard to methods applied and ecosystem services valued. In addition to providing a general synopsis, the two most widely used valuation methods—stated preference and abatement costs—will be examined in detail. Through our analysis, we have identified eight blind spots in the economic valuation of Baltic Sea ecosystem services that are related to countries, ecosystem services, and ecosystem-service interactions that have been neglected in the literature. Consequently, we discuss how these issues can be addressed by policy-makers and researchers while also pointing out the limitations of previously applied methods and identifying a need for more methodical work. Regardless of the ecosystem service valued, we found a need to develop a coordinated valuation strategy for marine ecosystem services in the Baltic Sea to provide consistent and meaningful policy recommendations. The present study is relevant for policy-makers, practitioners, and researchers for the following reasons: first, it provides a clearly structured overview of what data are available and which ecosystem services have been valued by which methods. For example, the limited availability of observed travel behaviour data seems to have forced researchers to use stated preference methods instead of revealed preference methods. Improving our knowledge of available data is indispensable for setting priorities for future data collection efforts (Bo¨rger et al., 2014). Second, revealing blind spots of ecosystem services valuation may provide guidance for defining future research directions. Research on the advancement of valuation methods regarding neglected ecosystem services is recommended to establish a more consistent valuation framework. Third, the paper provides applied researchers and policy-makers with an overview of the existing literature to facilitate conducting of further meta- and cost-benefit analyses.
Material and methods The data processed in this paper were collected from studies published in peer-reviewed international journals and final project reports from 1995 to the beginning of 2015. We searched Google Scholar using the following terms: Baltic Sea AND (valuation OR stated preferences OR revealed preferences OR abatement costs OR cost-benefit analysis.) This method provided more relevant
J. Sagebiel et al. results than Scopus or searching databases on marine ecosystem service valuation, such as http://www.marineecosystemservices. org/). Only studies fulfilling the requirement of using primary or secondary data to value at least one ecosystem service related to the Baltic Sea with an economic valuation method were taken into account. Considered methods include market price and cost-based methods as well as stated and revealed preference approaches. Studies relying primarily on meta-analysis and literature review were not incorporated, but studies based on already published results to conduct new analysis (e.g. benefit transfer, cost-benefit) were included. For comparison, all monetary values were converted to Euros using the average exchange rate from the year of publication, based on the online database OANDA (OANDA, 2015). Then, values were converted to price levels for 2014 and normalized for purchasing power using the harmonized indices of consumer prices and comparative price levels provided by EUROSTAT (Eurostat, 2015a, b). For ecosystem services classification, the approach from HELCOM (2010) was used (see the Ecosystem services classification and valuation section). Methods were usually named as mentioned in each study, but some methods were subsumed under a broader category, as they lacked sufficient observations. The scope included all nine states neighbouring the Baltic Sea (from now on riparian states): Denmark, Germany, Poland, Lithuania, Latvia, Estonia, Russia, Finland, and Sweden. As many publications have reported results for several riparian states, ecosystem services, and/or applied methods, the data were organized into a multilevel format, with each observation consisting of one unique combination of these three categories. For example, a publication assessing the value of recreation using the travel cost method and contingent valuation in Sweden was recorded as two observations, because two methods were used. Table 1 illustrates the data alignment used, including the just-explained example (number 35). The full table is available in the Supplementary Appendix and can be readily extended for meta-analysis.
Ecosystem services classification and valuation Since it is still the most common and frequently used classifi cation system, the approach from HELCOM (2010) and the Millennium Ecosystem Assessment Report (Millennium Ecosystem Assessment, 2005) was followed for categorizing ecosystem services into provisioning, regulating, cultural, and supporting services (Table 2). [There are some drawbacks to the HELCOM ecosystem services classification system that have implications for valuation (de Groot et al., 2002; Hein et al., 2006; Boyd and Banzhaf, 2007; Wallace, 2007; Fisher and Turner, 2008; Fisher et al., 2009). For example, ecosystem services are interdependent or overlapping (Kandziora et al., 2013).] As supporting ecosystem services generally set the basis for generation of the other services, many authors have regarded them as a special case, not integrated into their primary valuation, to avoid double counting (Hein et al., 2006). Authors have used a wide variety of methods to value ecosystem services (Haab and MacConnell, 2002; Freeman, 2003; Hanley and Barbier, 2009; TEEB, 2010), including market price and cost-based methods as well as revealed and stated preference methods. Market price methods are mainly concerned with estimating the welfare effects of shifts in demand and supply curves. Cost-based methods include assessment of abatement, damage, and replacement or substitution costs, out of which the abatement cost method has been used most frequently in the Baltic Sea context, often applied to estimate costs for reducing nutrient
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Economic valuation of Baltic marine ecosystem services Table 1. Example of data alignment from the multilevel analysis format used for this study. Study no. 33 34 34 35
Title Economic criteria for using wetlands as nitrogen sinks under uncertainty Economic valuation for sustainable development in the Swedish coastal zone Economic valuation of sport-fishing in Sweden
35
Year 2000
Country Sweden
Ecosystem service Reduction of eutrophication
Method Abatement costs
2005
Sweden
Recreation
Travel cost
2005 2004
Sweden Sweden
Habitats Recreation
Travel cost Contingent valuation
2004
Sweden
Recreation
Travel cost
Table 2. Classification of ecosystem services according to HELCOM. Provisioning ecosystem services Food Inedible goods Energy Space and waterways Chemicals Ornamental resources Genetic resources
Supporting ecosystem services Biogeochemical cycles Primary production Food web dynamics Biodiversity Habitats Resilience
Regulating ecosystem services Impact on climate and air quality Sediment retention Reduction of eutrophication Removal of nutrients Regulation of pollutants
Cultural ecosystem services Recreation Aesthetic value Science and education Cultural heritage Inspiration The legacy of the sea
Source: HELCOM (2010).
emissions to reduce eutrophication. Abatement cost values are derived from the costs of measures that seek to prevent emissions or immissions, such as reducing agricultural fertilization, restoration of wetlands, or investment in wastewater treatment plants. In general, however, cost-based methods lack a solid foundation in economic theory, as they only rely on changes in costs— thereby not accounting for market dynamics—and thus are unable to provide a full picture of welfare changes (Freeman, 2003). Welfare changes could be estimated with, for example, general equilibrium models, but often the additional value of such models usually does not justify the costs induced by significantly greater data requirements and computational efforts. Revealed preference methods include the travel cost method and hedonic pricing, both of which rely on observed data, such as the actual distances tourists have travelled to marine recreational sites and associated costs. Such methods make use of the assumption that ecosystem services create value that can be observed in related markets. High recreational value in some areas may, for example, be indicated by increased real estate prices compared with other areas. However, it is often difficult to trace back the sources of increased prices, as several other variables may affect real estate values (e.g. neighbourhood characteristics, access to public transport). Thus, such methods are only applicable when the data include sufficient uncorrelated control variables and independent observations. Meanwhile, stated preference techniques, most prominently discrete choice experiments and contingent valuation, can avoid such problems. They rely on survey-based data generated via hypothetical decision situations for certain groups of stakeholders and are especially useful when the valued ecosystem service is not tradable on
markets and, therefore, prices and quantities cannot be directly observed. (Stated preferences approache will be explained in more detail below). In some cases, results from existing revealed and stated preference studies are transferred to other areas, thereby adjusting important variables such as income, an approach called benefit transfer. While market price methods as well as revealed and stated preference methods are theory-driven and consistent with economic welfare theory (Freeman, 2003), cost-based approaches rely on empirical and pragmatic considerations. It is, hence, difficult to compare results which are produced by different methods (Hirschfeld and Sagebiel, 2014). Yet different ecosystem services require different valuation methods (Barbier, 2007, 2011; DEFRA, 2007; Bateman et al., 2011b; Bouma and van Beukering, 2015). Provisioning services usually produce goods that are physically tradable, such as fish, making the market price method most appropriate to measure their value. In contrast, the value of regulating services is usually not indicated by market prices, but cost-based approaches or stated preference methods can be used to provide appropriate approximations. The values of cultural ecosystem services only emerge through their (subjective) effect on the wellbeing of people, such as through the perceived value of recreation, and are best measured with revealed and stated preference methods. A more detailed discussion of advantages and disadvantages of these valuation methods is found in Brouwer et al. (2013). When it comes to cost-benefit analysis, different strategies exist for combining results from different methods (Cost-benefit analysis is not a valuation study in the sense intended here. But one can still use results of such analysis to indirectly value ecosystem services). One could, for example, use cost-based approaches for the cost side of the analysis and revealed and stated preference methods for the benefit side. Alternatively, stated and revealed preference methods can complement the cost side, such as when assessing the costs of a reduction in fish stock due to increased commercial fishing activities. In addition to loss of future incomes for fisheries and increased fish prices, stated preference methods can capture associated non-use values [non-use values are “monetary values on natural resources and environmental characteristics that are independent of any present or future use” (Freeman, 2003, p. 137)], allowing a more holistic picture of costs and benefits.
Results and discussion This section presents the results of the valuation studies considered in this paper, providing a comprehensive picture of ecosystem services valued and when, where, and how they were assessed. The first part analyses all of the studies, whereas the second and third parts examine in more detail those studies that have applied stated preference and abatement cost methods. We have decided against conducting a meta-regression because, first, in our case, there is
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no common effect size (dependent variable) which could be analysed with such methods. This argument mirrors our main critique of a lack of consistency in the economic valuation literature concerning the Baltic Sea—a key reason for writing this paper. Second, specifically for the Baltic Sea, the data are still too sparse to obtain statistically valid results. Extending the dataset to the whole of Europe or the entire world is not within the scope of this paper, but it has already been done (Nelson and Kennedy, 2009; Ahtiainen and Vanhatalo, 2012).
Overview In total, 76 studies were reviewed, leading to 388 observations, with an average study consisting of five observations (e.g. applying one method to value one ecosystem service in five countries). The average amount of studies conducted per year did not increase during the almost 20-year period studied, though there is some variation between years (Figure 1). Table 3 indicates the number of methods, ecosystem services, and riparian states each study has incorporated into its economic valuation. Only nine studies valued more than one ecosystem service, and none valued more than three services at once, indicating to us that Baltic Sea economic valuation studies have hardly incorporated ecosystem service interactions and related synergies. We will call this Blind Spot 1. Similarly, 59 studies reported results based on using only one method. Applying more than one method to a valuation exercise tends to increase costs and efforts enormously, as it often requires different datasets. Yet, such methodological contributions (e.g. recreational values can be measured using travel costs and cross checked with contingent valuation surveys) appear to be important for investigating the reliability and robustness of individual
methods as well as the overall validity of economic valuations (Blind Spot 2). Additionally, as explained in the Ecosystem services classification and valuation section, holistic valuation of an ecosystem service often requires several methods for capturing values for different stakeholders. This could be remedied by studies synthesizing existing results, but, to our knowledge, no such studies exist (Blind Spot 3). It is noteworthy that, in economic valuation studies in general, approaches using several methods and valuing several ecosystem services are still rather uncommon (Chan et al., 2012; Gilvear et al., 2013). Thus, the first three blind spots we have indicated come as no surprise. Recent research on benefit transfer has shown that there are large differences between riparian states that make it difficult to take results from one and draw conclusions for the whole area (Bateman et al., 2011a; Ahtiainen et al., 2015). In our data, only 25 out of 76 studies focused on all riparian states simultaneously, while 48 studies were carried out in only one state, and 3 studies were done in two or three states (Blind Spot 4). Studies conducted in all riparian states were mostly abatement-cost based (see the Abatement cost approaches to estimating costs for reducing Baltic Sea eutrophication section), relying on secondary data. In some cases, contingent valuation studies also investigated all states (see the Stated preference approaches for estimating the value of HELCOM Baltic Sea ecosystem services section).
Riparian states Marine ecosystem services were studied most frequently in Sweden, with 77 observations, followed by Finland, with 50. All other riparian states were relatively similarly covered, with between 34 and 41 observations each (Figure 2), which can be mainly attributed to the fact that several studies included all riparian states. Considering only studies that did not focus on all riparian states (the dark bars in Figure 2) reveals that seven out of nine states have been studied less than ten times (Blind Spot 5). Only Sweden and Finland have 43 and 16 observations, implying that the overall picture on economic values provided by the studies may be biased towards values from Scandinavia and it may, consequently, be difficult to draw conclusions concerning the whole Baltic Sea area. In future research, less frequently covered states could take a more prominent role to complement the rich data availability from other states. Alternatively, to obtain values valid for the whole Baltic Sea area, grant givers could concentrate on
Figure 1. Published Baltic marine ecosystem services valuation studies per year between 1995 and 2015. This figure is available in black and white in print and in colour at ICES Journal of Marine Science online. Table 3. Number of methods, ecosystem services, and riparian states incorporated into economic valuation studies of the Baltic Sea. Number of X per study X Ecosystem services analysed Methods used Riparian states included Total number of studies n ¼ 76
1 67 59 48
2 5 13 1
3 4 4 2
...
9 – – 25
Figure 2. Frequency of each riparian state being covered by valuation studies (1995 –2015), among all studies examined and for studies not covering all nine riparian states. This figure is available in black and white in print and in colour at ICES Journal of Marine Science online.
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Figure 3. Economic valuation methods used per Baltic Sea ecosystem service studied (1995– 2015).
supporting transboundary projects. In this respect, the BalticSTERN project (http://www.stockholmresilience.org/21/research/researchprogrammes/balticstern.html) and the recently relaunched European Union Bonus projects (http://www.bonusportal.org/) seem to be promising ways forward.
Ecosystem services Figure 3 shows the frequency of different ecosystem service valuations in absolute and relative terms. Reduction of eutrophication was by far valued most frequently (327 times), using the abatement cost method (194 times), stated preference methods (57 times), benefit transfer (39 times), and cost –benefit analysis (22 times). This appears to be due, first, to eutrophication being a major issue in the Baltic Sea (Gren et al., 2000) and, second, because changes in the status of eutrophication have tangible effects for various stakeholders. The great focus on reduced eutrophication is therefore no surprise. Yet, although the Baltic Sea is also quite vulnerable to the adverse effects of pollutants and heavy metals—related to the ecosystem service “regulation of pollutants” (EMEP, 2013)—this ecosystem service has only been valued twice and only with stated and revealed preference methods (Blind Spot 6). Recreation has been valued 29 times, usually with stated preference methods (Figure 3). Interestingly, food, a provisioning service, has been valued 17 times with several methods, including stated preference methods and cost-based approaches, though here the market price method seems most suitable. However, as with eutrophication, changes in the production of food—primarily fish in the Baltic Sea context—have implications for other ecosystem services. For example, there may exist non-use values for certain species of fish that market price methods cannot capture. Only stated preference methods can measure such non-use values. It thus seems obvious that interactions between ecosystem services are important for economic valuation, with the example of fish showing that different methods may be required to capture the total economic value of individual ecosystem services. We now come to the somewhat surprising fact that several ecosystem services have not been valued at all. Some may be difficult to measure (“genetic resources”, “inspiration”), not threatened or not alterable (“space and waterways”). Yet others are quite important, and it is unclear why they have so often been ignored. Consider
Figure 4. Frequency of economic valuation methods applied for valuing marine ecosystem services related to the Baltic Sea region (1995 – 2015). This figure is available in black and white in print and in colour at ICES Journal of Marine Science online.
“energy”, a provisioning ecosystem service. Although there is a large body of literature on offshore wind and geothermal energy, and offshore wind energy has been abundantly valued with stated preference methods, it has not been discussed within the ecosystem services context. Rather, such studies have mainly been focused on the aesthetic disadvantages of the visibility of these technologies and, if at all, fit better into the classification of cultural ecosystem services concerning “cultural heritage” and “aesthetic value” (Ladenburg and Dubgaard, 2007, 2009; Haggett, 2011). Five observations were concerned with “biodiversity” and two with “habitats”, both supporting ecosystem services. As explained earlier, however, researchers have suggested not including supporting services to avoid double counting, demonstrating inconsistencies in valuation approaches as well as their complexity.
Methods Abatement cost has been the most frequently applied method, with 194 observations (Figure 4), and was exclusively applied for reduction of eutrophication. The damage cost method has been used 13 times and replacement cost three times. Authors have less frequently used stated preference methods compared with abatement cost ones: our data include 78 observations for contingent valuation studies and 12 observations for discrete choice experiments. Meanwhile, revealed preference methods have rarely been used (six times for the travel cost method and once for hedonic pricing), which may be caused by limited data availability (Blind Spot 7). In the UK, a large panel dataset on the recreational activities of UK residents is readily available (Natural England, 2015), that has enabled thorough analyses to be undertaken using the travel cost method (Bateman et al., 2013; Sen et al., 2014). In contrast, similar data regarding the Baltic Sea are at present rather limited, which may be the reason for the infrequent application of revealed preference methods. Altogether, stated and revealed preference methods were used 97 times to value various ecosystem services, including biodiversity, habitats, recreation, and reduction of eutrophication. Discrete choice experiments have been especially useful here, as they allow the inferring of preferences for different ecosystem services within a single survey. The rarely used revealed preference methods were exclusively focused on recreation.
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Benefit transfer, as a low-cost alternative to primary data collection, was found 40 times. Earlier applications of this method have often, however, been contested as providing inaccurate results, making it difficult to rely on such studies, especially if their values are incorporated into cost-benefit analysis (Blind Spot 8). Nonetheless, recent methodological developments regarding this approach seem promising and may provide new ways to obtain more reliable economic values (Bateman et al., 2011a; Johnston et al., 2015). Cost-benefit analysis had 22 observations (from six studies) in our data and other methods that cannot be categorized with those explained in the Ecosystem services classification and valuation section totalled 14 observations, coming from 6 studies. These included calculation of net present values, other cost-based approaches, and estimations of demand elasticities.
Synthesis The above analysis has revealed what we consider to be eight blind spots in the economic valuation literature regarding the Baltic Sea, the key ones being riparian states not sufficiently covered, neglected ecosystem services and ecosystem service interactions, and limited employment of multiple methods. Funding bodies, such as the European Union and national governments, as well as researchers will now hopefully take the opportunity to steer their
activities towards attacking these blind spots, which Table 4 summarizes in more detail. Funding agencies could support research that helps to fill gaps here while also aiming at establishing a Baltic Sea-specific platform to collect and communicate the results of past and future Baltic Sea economic valuation studies. It is also possible for existing platforms to integrate such results. HELCOM, for example, provides geo-referenced data and maps assessing various ecosystem services, yet provides no estimates of their value (http ://www.helcom.fi/baltic-sea-trends/data-maps). Researchers can make use of the already existing valuation data, such as from Sweden, to conduct further secondary analyses while also focusing their actions towards regions and ecosystem services that have been less frequently valued. Further, they can tackle emerging issues such as the incorporation of interactions between ecosystem services and make use of state-of-the-art methodological advances in areas such as benefit transfer. Finally, all relevant actors can try to work towards building an economic valuation framework that can serve as a basis for future research activities.
Stated preference approaches for estimating the value of HELCOM Baltic Sea ecosystem services Stated preference applications comprise contingent valuation surveys and discrete choice experiments. In contingent valuation, respondents state their willingness to pay for an improved scenario,
Table 4. Blind spots located within the Baltic Sea ecosystem services economic valuation literature (1995 – 2015) and possible responses from policy-makers, funding agencies, and researchers. n Blind spots 1 Interactions between ecosystem services are often neglected, as 67 of 76 studies valued only one ecosystem at a time 2 Different methods are required to value one ecosystem service (see reduction of eutrophication and food), though 59 of 76 studies only used one method
Possible responses from funding agencies Incorporate modelling of ecosystem services interactions in new projects
Possible responses from researchers Use valuation methods (e.g. discrete choice experiments) that can account for interactions Consider using various methods to value a particular ecosystem service. Increase cooperation with researchers from other fields
Enlarge the role of valuation in such projects, and encourage researchers with expertise in different kinds of methods to participate, taking into account that additional costs can arise Support projects that synthesize existing Develop a framework for arriving at a holistic economic valuation data; establish a platform economic valuation scenario that collects and makes available all economic valuation studies concerning the Baltic Sea
3 There are no synthesizing studies that bring together results from previous studies, although such studies could be used towards obtaining a holistic valuation of ecosystem services 4 Conclusions for the Baltic Sea as a whole cannot Support projects that conduct research in all be easily drawn from results from one riparian states; strengthen European country; yet only 33% of the reviewed studies Union-wide collaboration incorporated all nine riparian states 5 All states beside Sweden and Finland have been Focus primary data collection support to areas valued less than ten times individually, which with limited existing valuation data may create a bias of values towards Scandinavian preferences
6 Several ecosystem services have not been valued Identify further ecosystem services that are at all relevant for EU directives concerning the Baltic Sea, and support research activities for them 7 Revealed preference methods have been used Similarly to the UK, centrally organized primary only seven times, possibly attributable to low data collection should be supported data availability. 8 Benefit transfer has been used, but recent Support further methodological research on methodological advances have revealed benefit transfer several inaccuracies in the estimated values, questioning its validity
Frame new research in ways such that it can be compared with existing results
Use existing data in Sweden for further analysis (e.g. cost–benefit). Apply newer benefit transfer methods to transfer values from Sweden and Finland to less explored countries, and especially test their accuracy Develop/apply methods that can be used to value such ecosystem services
Use existing data if possible, and complement stated preference studies with revealed preference methods Do not rely too much on older benefit transfer studies; make use of recent advances to obtain more accurate results
6 –75 6 –75
47– 181 47 –181
Sweden
Poland
All riparian states
¨ stberg et al. (2012) O
Ressurreic¸a˜o et al. (2012)
Ahtiainen et al. (2014)
Reduction of eutrophication
Reduction of eutrophication
CVM
Not specified Onetime payment pP Infinite Yearly tax pP CVM
19– 54 3 –10 Monthly fee pHH 20 years CVM
WTPa pP and year 309 385 61– 150 57– 88 120 50– 107 155 –201 83 WTPa 309 385 61 –150 57 –88 10 50 –107 325 –423 166 Payment vehicle Yearly tax pP Yearly tax pP Yearly tax pP Yearly fee pP Monthly payment pP Yearly fee pP Yearly fee pHH Yearly fee pHH Period Not specified 20 years 10 years 1 year 10 years 1 year 20 years Not specified Method CVM CVM CVM CVM CVM DCE DCE DCE
Ecosystem service Reduction of eutrophication Reduction of eutrophication Reduction of eutrophication Recreation Reduction of eutrophication Biodiversity, recreation, food Recreation, aesthetic value, food Recreation, regulation of pollutants, food Habitats, reduction in eutrophication Biodiversity Benefit Reduction of eutrophication Reduction of eutrophication Reduction of eutrophication Recreational fishing Reduction of eutrophication Improvement of water qualityb Improvement of water qualityc Improvement of oil-spill managementa Improved water quality/reduction in noise and litter Prevention of species loss (3 levels) Riparian state Poland Sweden Poland, Lithuania Denmark, Sweden, Finland Denmark Sweden Finland Germany Reference Z˙ylicz et al. (1995) Gren et al. (1997) Markowska and Z˙ylicz (1999) Toivonen et al. (2004) Atkins and Burdon, (2006) Eggert and Olsson (2009) Kosenius (2010) Liu and Wirtz (2010)
Table 5. Studies using stated preference methods to value HELCOM Baltic Sea ecosystem services (1995 – 2014).
compared with baseline or status quo ones. Researchers can use a variety of elicitation formats, which one can broadly categorize into open-ended and closed-ended questions. With open-ended questions, respondents can freely state a willingness to pay value, while in closed-ended formats, they can either choose from a set of given values (payment card) or can agree or disagree to pay a fixed amount (dichotomous choice). In contrast, in discrete choice experiments, respondents choose among alternatives that differ in terms of their characteristics or attributes, one of which is a monetary one, such that respondents face a trade-off between the other attributes and the costs. The method has the advantage that each attribute can be assigned an individual monetary value. Thus, researchers can elicit more detailed information on people’s preferences and infer values for different ecosystem services simultaneously. [The introductory literature on discrete choice experiments and contingent valuation is abundant. Readers are referred to Alberini and Kahn (2006), Freeman (2003), Haab and MacConnell (2002), and Louviere et al. (2006).] Among the stated preference applications used for the Baltic Sea, 11 studies estimated willingness to pay for improvement of water quality (Table 5). Five of these studies explicitly referred to reduction of eutrophication, while the others used other ecosystem services—biodiversity, habitats, food, aesthetic value, recreation— to describe water quality. Three studies used discrete choice experiments and the remaining ones contingent valuation. Gren et al. (1997) conducted the first contingent valuation survey with multiple countries. They included data from an earlier Swedish contingent valuation survey and used the estimated values to generate willingness to pay values for all other non-ex-socialist riparian states. They also included values from Poland and Lithuania, taken from an earlier draft of Markowska and Z˙ylicz (1999) and Z˙ylicz et al. (1995). Other studies that have directly focused on reduction of eutrophication are Atkins and Burdon (2006), who used the Randers Fjord in Denmark as a case study, and Ahtiainen et al. (2014), who have conducted the largest Baltic Sea contingent valuation study undertaken to date, covering all nine riparian states and with over 10 000 respondents. Other contingent valuation publications have not exclusively focused on reduction of eutrophication. ¨ stberg et al. (2012), for example, valued improved water quality O defined as reduced noise and litter at recreational sites within the context of Special Conservation Zones and the EU Water Framework Directive. Meanwhile, Toivonen et al. (2004) estimated willingness to pay for recreational fishing, and Ressurreic¸a˜o et al. (2012) focused on biodiversity by investigating willingness to pay for species loss. Within the discrete choice experiment studies, different ecosystem services were simultaneously covered. Eggert and Olsson (2009)—the first discrete choice experiment study for the Baltic Sea context—used coastal cod stock, bathing water quality, and biodiversity as attributes, thereby capturing economic values for the ecosystem services food, recreation, and biodiversity in Sweden. Konsenius (2010) conducted a discrete choice experiment in Finland regarding various attributes representing the ecosystem services recreation, aesthetic value, and food, whereas Liu and Wirtz (2010) used Germany as a case study to assign values for the improvement of oil spill management, using a discrete choice experiment to cover the ecosystem services recreation, regulation of pollutants, and food. A closer look at estimated willingness to pay values reveals high variance among them as their overall framing, the goods to be
WTP, willingness to pay; CVM, contingent valuation method; DCE, discrete choice experiment; pP, per person; pHH, per household; CPL, comparative price levels. Attributes include coastal waters protected from oil pollution, beaches avoided from oil pollution, Eider ducks avoided from oil pollution, collect ratio of spilled oil to be collected by combat vessels, yearly payment for using combat facilities. a All WTP’s are given in EUR2014 based on CPLEU-28. b Attributes include coastal cod stock levels, bathing water quality, and biodiversity levels. c Attributes include water clarity, abundance of coarse fish, status of bladder wrack population, mass occurrence of blue–green algae blooms.
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998 valued, applied methods, and time frames differ. We tried different meta-regressions with the available data, but the limited number of observations and high correlations among explanatory variables did not allow drawing of statistically valid conclusions. Still a descriptive analysis reveals some insights. It is notable that, even between studies that appeared similar in their framing, the resulting values differed significantly. For example, Ahtiainen et al. (2014) estimated willingness to pay for a 50% reduction of eutrophication at between 6 and 75 EUR per person and year while, for the same reduction and periodicity, Gren et al. (1997) came to a value of 385 EUR, and Markowska and Z˙ylicz (1999) estimated willingness to pay as being between 61 and 150 EUR. These differences may come from a historical change in preferences (18-year difference between Gren et al. and Ahtiainen et al.) or may be due to methodological standards that have changed over the years but which are not related to changing preferences. For example, recent studies have frequently used online panels, while earlier studies used in-person or telephone interviews (Lindhjem and Navrud, 2011). Willingness to pay is further influenced by the assumptions researchers make. Sometimes they want to obtain conservative estimates of willingness to pay to avoid critique of inflated values or just to provide lower bounds (willingness to pay is larger than . . .). An interesting example is the study by Gren et al. (1997), where the authors used Polish willingness to pay values from Z˙ylicz et al. (1995). Unlike the reported values in Z˙ylicz et al., they assumed nonresponses as zero willingness to pay values. As the response rate was 50%, willingness to pay was consequently halved in their study. This example demonstrates the challenge of understanding economic valuation studies. In decision-making processes, it is difficult for policy-makers to elicit meaningful values from such studies, as there are no clear guidelines and several assumptions have to be made. A sensitive characteristic of stated preference studies is payment vehicle, that is, the way the respondent is supposed to pay for a proposed improvement (Morrison et al., 2000; Ivehammar, 2009). Proposed payment vehicle definitions varied strongly among Baltic Sea valuation studies. For instance, three studies referred to willingness to pay of households, whereas the remaining eight studies referred to per-person values. Four studies referred to a “tax”, while the others referred to a “fee” or “payment”. Further, the studies differed in terms of their periodicities, meaning the time frames within which proposed payments are to be made. Two studies considered a one-time payment, five studies focused on a period between 10 and 20 years, one study had an infinite periodicity, and three studies did not report their periodicity. Recent work on stated preference methods has revealed further methodological challenges that influence welfare estimates, including protest responses, i.e. cases where respondents do have a willingness to pay but state it to be zero, because they have constraints that prevent them from revealing their true willingness to pay (Meyerhoff and Liebe, 2008), experimental design complexity (Meyerhoff et al., 2015; Weller et al., 2014; Oehlmann et al., 2014), and elicitation format (open vs. closed ended) in contingent valuation (Kealy and Turner, 1993). We cannot draw further conclusions on whether willingness to pay in the studies presented here are influenced by such methodological challenges but can at least note, based on findings from the literature, that they do exist in general. We do conclude that it is cumbersome for policy-makers to use the currently available results for practical planning activities and for researchers to incorporate them into cost-benefit analyses, as it would seem hardly possible to trace back the reasons for the various outcomes they are confronted with.
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Abatement cost approaches to estimating costs for reducing Baltic Sea eutrophication In the literature, the abatement cost method was exclusively used for estimating the costs of measures to reduce eutrophication, with two research questions being dominant. The first question focused on comparison of costs for individual measures to reduce eutrophication, whereas the second dealt with the identification of costeffective or coordinated solutions (i.e. where all countries cooperate on an overall cost-effective reduction option). While the first question is more general, the second can be considered to be seeking a scientific response to the Baltic Sea Action Plan, as most studies applied different models to identify strategies that may help in achieving its goals at minimum cost. These research questions are of course interrelated, as applying most cost-efficient measures is a prerequisite for achieving cost-effective reduction of eutrophication. Concerning the first research question, most studies distinguished between agricultural land use measures, such as improved fertilization techniques, cultivation of catch crops and restoration of wetlands, and direct abatement measures, which had a primarily technical character, such as increasing capacities of wastewater management in purification plants. Costs of land use changes were assessed by estimating opportunity costs for alternative land uses (Gren, 2008a). The costs of reducing the use of fertilizers were usually calculated as the change in farmers’ surplus that would result from a given reduction in fertilizer application (Kiirikki, 2003). Direct measures were generally assessed based on econometric methods, estimating the additional costs that arise when a measure is implemented (Gren et al., 1997, 2000). Costs for direct abatement measures ranged between 2 and 86 EUR kg21 of abated nitrogen, between ,1 and 243 EUR kg21 of abated phosphorus, and between 2 and 25 EUR kg21 for the abatement of both nutrients (Table 6). The most cost-efficient measures for nitrogen reduction were improved fertilization techniques, restored wetlands, and improved treatment of wastewater, whereas for phosphorus reduction, they were the use of phosphate-free detergents and more effective wastewater treatment. Although most studies provided values per kg and used similar measures, direct comparability was not always given, as they differed in terms of examined nutrients (either nitrogen or nitrogen and phosphorus), reduction targets, discount rates, as well as quantity and specification of measures. This comparability problem becomes obvious when considering the wildly differing highs for abatement costs of only one nutrient compared with the relatively low upper limit for abating both. The policy background for the second research question regarding the identification of cost-effective abatement solutions is commitment to a preliminary nutrient-reduction scheme agreed upon by all riparian states in 2007, based on the concept of setting maximum allowable nutrient inputs in water and air necessary to reach good environmental status for the Baltic Sea (see HELCOM (2013) for more details). Parallel with the HELCOM targets, several studies compared regionally differentiated coordinated solutions with unilateral solutions (Table 7). A coordinated solution means that all riparian states would cooperate on an overall cost-effective reduction option. Meanwhile, a unilateral solution means agreement to a policy with uniform proportional load reductions (Gren, 2008b). Such policies have been common for nitrogen reduction regarding the Baltic Sea, where riparian states have agreed to reduce their loads by a certain proportion in relation to their initial loads (Hjorth, 1992). A
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Economic valuation of Baltic marine ecosystem services Table 6. Studies calculating abatement costs for various measures to reduce nutrient immissions into the Baltic Sea (2000 – 2012). Riparian state
Reduction target
Sweden
50%
Kiirikki (2003)a
Finland
2100 t year21
Larsson et al. (2005)b Helin et al. (2006) Schou et al. (2006)c
Sweden Finland All
21% 50% 160 000 t
Reference Nitrogen Bystro¨m (2000)
Results in million EUR2014 (CPL) per year
Discount Costs in EUR2014 rate (CPL) kg21
64 89 – – – 35–48 60/895/12
– – 3% 3% – – 3%
13 17 6 28 5 7–9 2
– – 34
– – –
47–102 13 10d
25%
Sewage Detergents Sewage Agriculture
207 – 35
3% – – –
Below 1 64 132 –280 345d
50%
Agriculture
1489
–
4d
50%
Sewage Agriculture Combination and additional measures Agriculture/wetlands/ sewage/detergents
484 –1155 1402 3525
– – –
– – 25
1476
3.5%
2d
HELCOM and NEFCO (2007) All
50%
Mewes (2012)
25%
Germany
Phosphorus Finland Kiirikki (2003)a HELCOM and NEFCO (2007) All Mewes (2012)
Germany
Nitrogen and phosphorus simultaneously Elofsson (2003) Sweden, Russia, Poland HELCOM and NEFCO (2007) All
Ahlvik et al. (2014)e
All
62 t year21 50%
50%
Measures Wetlands Agriculture Sewage Agriculture Agriculture Agriculture Wetlands/agriculture/ sewage Sewage Agriculture Agriculture
a
All results are for nitrogen equivalents. Cost calculations are divided into farm short-term, farm long-term, and social costs. c Deprecation period of 20 years. d Based on own calculations from data provided by Mewes, 2012 (average value from different regions) and Ahlvik et al., 2014 (total costs/total kg N + P). e Computation of the least-cost solution to reach good environmental status of the Baltic Sea (according to BSAP) within 40 years. b
central finding of these studies is that it appears to be worthwhile to focus nutrient-abatement efforts on economic sectors, riparian states, and regions within those states, which have the greatest potential for nutrient reduction (Ahlvik et al., 2014). The most costeffective measures have been reported to be restoring wetlands and increasing the capacities of wastewater management in purification plants and cultivation of catch crops. The nitrogen abatement costs for a unilateral solution at a 50% reduction target were only reported in Ollikainen and Honkatukia (2001), at 242 EUR kg21 nitrogen being abated. For the same reduction target, the costs of the coordinated solutions ranged between 1 and 162 EUR kg21. Abatement costs at a 50% reduction target for phosphorus ranged between 70 and 650 EUR kg21 for a unilateral solution and 0 to 352 EUR kg21 for a coordinated solution. Similar to our observations regarding stated preference approaches, the abatement cost studies also differed in terms of the details of the methods used. Different reduction targets and various ways of estimating the success of implemented measures make comparisons difficult. Another challenge was the observation of two nutrients (phosphorus and nitrogen) in some studies and only one in others. Additionally, costs per kg increase with rising ambitions of the selected reduction target. Due to these increasing marginal costs of abatement, reduction costs per kg are lower for a 20% reduction target than for a 50% one. Thus, comparing such values would require accounting for the often not clearly understood non-linearities of abatement costs.
Conclusions In this paper, a total of 76 empirical studies conducted between 1995 and 2015 focusing on marine ecosystem service valuation in the Baltic Sea area have been considered. Two findings from our analysis appear to be especially relevant for policy-makers and researchers who plan to conduct or investigate valuation studies in the future. First, there is an imbalance among ecosystem services valued and countries covered. While the regulating ecosystem service reduction of eutrophication and the cultural ecosystem service recreation have frequently been the subject of valuation studies, thus far most Baltic Sea marine ecosystem services, as categorized by the HELCOM commission, have only rarely been valued or have not at all been the subject of economic assessment. Since information in monetary terms is usually easy to understand and an essential part of political decision-making, increased efforts should be made to undertake studies on the economic valuation of such understudied marine ecosystem services. Further, the number of conducted studies among the different riparian states varied strongly. While data availability in Scandinavian countries has been rather plentiful, authors have hardly covered Eastern European countries. Consequently, estimated values based on these data have had only limited capability when formulating statements regarding the Baltic Sea riparian states in general. Another blind spot is related to the treatment of interactions between
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J. Sagebiel et al.
Table 7. Studies on coordinated vs. uniform abatement costs for the reduction in nitrogen and phosphorous immissions into the Baltic Sea (1997 – 2010). Result in million EUR2014 (CPL) per year
Cost in EUR2014 (CPL) kg21
Reference Nitrogen Gren (2001) Ollikainen and Honkatukia (2001) Gren (2008a) Elofsson (2010b)d
Reduction target
Number of measures
Unilateral
Coordinated
Unilateral
Coordinated
50% 50% 0 –50% 24%
– – 14 14
4318a 140 084 – 4858
2689a 21 072 ,3300c 4082
– 324a 1 –75
1–217 48b 30c 0–71
Phosphorus Ollikainen and Honkatukia (2001) Gren (2008a) Elofsson (2010b)d
50% 0 –70% 50%
– – 10 8
10 229 – 4858
1094 ,2 200c 4082
301b – 75– 697
32b 211c 0–377
21
659 –6500
110 –1810
–
5b
Nitrogen and phosphorus simultaneously Gren et al. (1997) 50% a
Cost–benefit analysis; figures are net-costs. Based on our own calculations from data provided by Ollikainen and Honkatukia (2001): total costs/total kg N and P. Figures are based on a 50% reduction target. d Elofsson reports zero marginal costs for those basins where only one nutrient is binding, i.e. the other is abated “for free”. b c
ecosystem services. While such interactions have been emphasized in the literature on ecosystem service assessment and in the natural sciences (Bennett et al., 2009), nearly all of the Baltic Sea valuation studies that we analysed neglected their combined effects—positive and negative—thus hindering a more comprehensive understanding of the values of ecosystem services. In addition, no synthesizing study aimed at bringing together estimated values from different ecosystem services was found, making a holistic view on ecosystem service values hardly possible. Second, the analysis conducted here of stated preference and abatement cost studies has shown that there is great variation in estimated values, making it difficult for policy-makers to predict benefits and costs, such as concerning measures for reduction of eutrophication. The blind spots we have pinpointed appear to have strong implications for cost–benefit analyses, as not incorporating important values may lead to biased results when adding up the costs and benefits of a measure and, consequently, may lead to imprecise or even misguided policy recommendations. Using meta-analyses which incorporate methodological, regional, and other variables to explain estimated values may be a good means for obtaining more reliable results (Nelson and Kennedy, 2009). However, meta-analyses require a large number of observations, and the number of stated preference studies related to ecosystem services in the catchment area of the Baltic Sea is not yet sufficiently large. Additionally, the “effect size”, the dependent variable in a meta-regression, needs to be the same across studies, which does not hold true for the presented cases. As a consequence, authors primarily provided literature reviews instead of meta-analyses (Elofsson, 2010a; Bertram and Rehdanz, 2013). To establish a sound basis for comparable primary studies and subsequent meta-analyses and cost–benefit analyses regarding the Baltic Sea region, a more unified valuation framework is required. In the early 1990s, the National Oceanic and Atmospheric Administration Panel developed general guidelines for conducting contingent valuation studies (Arrow et al., 1993). A similar approach adapted to the Baltic Sea is justified because, compared with other seas, the Baltic Sea is more vulnerable to eutrophication and its consequences due to it being semi-brackish and having limited water exchange, combined with large-scale industrial and agricultural activities in the
riparian states (Gren et al., 2000). In other EU policy contexts, for example the Water Framework Directive, initial attempts have already been made in this direction (Brouwer et al., 2009), but making greater efforts towards developing a more systematic and reliable economic valuation methodological toolbox for marine ecosystem services could provide more transparent information for policy-makers seeking to find efficient solutions to improve the environmental status of the Baltic Sea’s marine environment. Finally, it is important to mention that the Baltic Sea is well covered with economic valuation studies compared with other seas and several issues we have mentioned here are of general nature and valid for other geographical areas. Thus, our overall recommendation is not necessarily to increase the number of valuation studies, but rather to aim for a more coordinated future research agenda, which fills the existing gaps, while making use of the large body of values that already exist. We propose that neglected riparian states such as the former socialist countries should become the focus of new research or, alternatively, new projects should be set up in a transboundary manner to cover all riparian states similarly. Research focus should also be placed on neglected ecosystem services such as regulation of pollutants, to complement already existing values such as those for the ecosystem service reduction of eutrophication. Methodological challenges should also be tackled from all sides. Standards for different valuation methods could be established, such as guidelines for the use of payment vehicles in stated preference studies. Developing a holistic picture covering all riparian states and ecosystem services should be a stated aim of European Union research activities, as only then will sound policy recommendations become possible, based on more accurate identification of ecosystem services that require additional resources for their protection. With a more comprehensive picture of where help is most crucially needed, measures for improving the state of the Baltic Sea can then be targeted more specifically and more accurately.
Supplementary data Supplementary material is available at the ICESJMS online version of the manuscript.
Economic valuation of Baltic marine ecosystem services
Acknowledgements We gratefully acknowledge support from the German Ministry for Education and Research within the SECOS (Grant Number: 03F0666) and KLIMZUG-RADOST (Grant Number: 01LR0807H) projects. Special thanks go to Eva-Maria Brodte for comments on an earlier draft as well as to Carolin Hoffmann, Daniel Bo¨ss, Heinrich Bo¨ing, and Stefanie Doll for support in preparation of the manuscript. We are also grateful to Christopher Hank for several comments on content and language. Finally, we thank the editor Claire Armstrong and two anonymous reviewers for their valuable comments.
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