AN INSIGHT INTO THE ECONOMIC VALUE OF REEF ENVIRONMENTS THROUGH THE LITERATURE: THE CASE OF THE SEAFLOWER BIOSPHERE RESERVE

UNA PERSPECTIVA DEL VALOR ECONÓMICO DE LOS AMBIENTES CORALINOS A TRAVÉS DE LA LITERATURA: EL CASO DE LA RESERVA DE BIOSFERA SEAFLOWER

Luz Londoño-Díaz and Myriam Vargas-Morales

Instituto de Investigaciones Marinas y Costeras (Invemar). Calle 25 No. 2-55 Playa Salguero, Santa Marta, Colombia. luz.londonio@gmail.com, me.vargas374@gmail.com.

ABSTRACT

The Seaflower Biosphere Reserve (SBR) is one of the few places in Colombia with a set of available studies on the economic value of its reef environments. This paper seeks to review the policy applications of these studies, and evaluate the use of benefit transfer (BT) methods to predict value estimates for sites in the SBR where no valuations have been performed. First, the paper provides an analysis and categorization of policy uses of existing results. A set of economic valuation studies were identified as somewhat influential in policy applications, because they provided financial sustainability tools for marine protected areas. A case study was selected from the pool of influential studies in order to assess the viability of BT. Second, the viability of using BT for determining recreational values of coral reefs within the SBR was assessed by: i) implementing a demand function transfer between the Johnny Cay Regional Park and the Old Providence and McBean Lagoon National Park; and ii) by estimating a meta-analytic function transfer based on world-wide meta-data on the recreational value of coral reefs. Results suggested a potential for the use of BT to predict recreational values for coral reefs in the SBR. In particular, the meta-analytic results indicated low to moderate transfer errors for the SBR, suggesting the viability of this approach.

KEYWORDS: Archipelago of San Andrés, Old Providence and Santa Catalina, Economic valuation, Benefit transfer, Coral reefs, Decision-making.

RESUMEN

La Reserva de Biosfera Seaflower (RBS) es uno de los pocos sitios en Colombia que cuenta con un conjunto de estudios disponibles en valoración económica de ambientes coralinos. Este artículo busca revisar las aplicaciones de política de tales estudios y evaluar el uso de métodos de transferencia de beneficios (BT) para predecir estimaciones de valor en sitios de la RBS donde no se han desarrollado valoraciones. Primero, el artículo provee un análisis y categorización de usos de política de los estudios existentes; se identificó un conjunto de estudios de valoración económica con influencia potencial en aplicaciones de política mediante la provisión de herramientas de sostenibilidad financiera para Áreas Marinas Protegidas. Seguidamente, se seleccionó un estudio de caso del conjunto de estudios con potencial de influenciar la toma de decisiones con el fin de evaluar la viabilidad de BT, mediante: i) la implementación de una función de transferencia de valor entre el Parque Regional Johnny Cay y el Parque Nacional Old Providence y McBean Lagoon; y ii) a través de la estimación de una función de transferencia meta-analítica con base en meta-datos mundiales sobre el valor recreacional de los arrecifes coralinos. Los resultados sugieren el uso potencial de BT como una nueva aplicación basada en los estudios existentes en la RBS. En particular, los resultados meta-analíticos indican errores de transferencia bajos y moderados para la RBS, sugiriendo la viabilidad de esta aproximación.

PALABRAS CLAVE: Archipiélago de San Andrés, Providencia y Santa Catalina, Valoración económica, Transferencia de beneficios, Arrecifes coralinos, Toma de decisiones.

INTRODUCTION

The Seaflower Biosphere Reserve (SBR) is located in the Archipelago of San Andrés, Old Providence and Santa Catalina, Colombia (Figure 1), in the western Caribbean Sea. It encompasses coastal and marine resources, including coral reef structures. One of them, the Old Providence barrier reef, is one of the largest coral reefs in the Americas, with a length of 32 km and an area of 255 km² (Unesco, 2011). It was designated a Unesco Biosphere Reserve in 2000, in order to promote sustainable development and alleviate problems associated with overpopulation, environmental degradation and poverty. The islands in the Archipelago are small, with high population density, which ranges from 283 inhabitants/km² in Old Providence to 2595 inhabitants/km² in San Andrés in 2013 (DANE, 2013a; Gobernación del Archipiélago, 2013). Similar to many coastal areas around the world, the economy of these islands relies heavily on marine resources as sources of income and employment, particularly from tourism, commercial shipping, and fisheries. In 2012, 49% of the added value of the Archipelago's economy was derived from tourism, trade and fisheries (DANE, 2013b). However, these benefits are not without cost. Internationally, there is a concern about the growing conflicts between outdoor recreational tourism and conservation (Shrestha and Loomis, 2001). This also applies to the SBR; James (2008) reported the environmental degradation in Johnny Cay Regional Park (JCRP) (Figure 2) as partially related to the high number of visitors and the anchoring of boats.

Attempts to achieve the multidimensional goals implicit in the SBR designation have been traditionally supported by scientific and technical research, mostly on biophysical aspects. More recently, these endeavors are also being supported by the emergent view of interconnectedness between environmental problems and social wellbeing. Under this perspective, economic valuation can play a key role in understanding environmental problems and improving management policies (Daily et al., 2009; TEEB, 2009). In the SBR, the use of non-market valuation is relatively recent. The first application can be traced to the late 90s with a study from Morales (1998) on the aesthetic value of Old Providence Island (Figure 2); since then an increase in the number of valuations has been observed for the SBR. However, challenges persist with regards to the use of valuation estimates to guide policymaking. A better understanding of the policy applications of existing results in the literature is necessary, before new studies are proposed. Conducting new valuations is expensive and demanding in terms of technical capabilities. In this case, benefit transfer (BT) is proposed as an alternative (Shrestha and Loomis, 2001). BT is defined as the transfer of a value estimate from a study site to a policy site where an estimate is not available (Johnston and Rosenberger, 2010). With this in mind, the contribution of this paper is to first identify what has been valued in the SBR and provide insights into policy uses of the existing valuation results. Secondly, we seek to explore the prospect of BT as a new policy use in the SBR through demand function transfer (DFT) and meta-analysis (MA). The demand function is tailored to transfer a value estimate from JCRP to the Old Providence and McBean Lagoon National Park (OPNP) (Figure 2), where such results are not available. The meta-analytic BT is implemented by adapting a function based on several study sites from around the world, to predict a value estimate for the SBR.

MATERIALS AND METHODS

Data used in this article come from secondary sources. With the exception of James (2008), all the studies reported in Table 1 correspond to grey literature, primarily theses. As the first methodological procedure, a qualitative review of studies on economic valuation of coral reef environments in the SBR was performed. Each study source was analyzed considering the following three factors: i) valuation object (commodity and type of value), ii) methodology and iii) uses in policy contexts. This discussion follows the categories of policy applications provided by Billé et al. (2012). In addition, these studies were evaluated in terms of the information they provided for the purposes of BT. James (2003) was selected as a case study, as it defined a specific commodity valued at a specific site within the SBR, and included a full definitions of methods, variables and functions. Other studies simultaneously valued a broader set of commodities or studied geographically more extended areas (e.g. the entire archipelago).

Next, a quantitative approach to the literature review was used by implementing both DFT and meta-analytic BT. Specifics of both methods are presented in the next two sections. All monetary variables were expressed in constant prices from the year 2000, by using the country-specific consumer price index (CPI) with 2000 as base year (United Nations, 2009). For cases where the original sample was applied to United States (US) visitors or foreigners, the US CPI was used. Finally, all values were expressed in international dollars by using the Purchasing Power Parity (PPP) exchange rate for the year 2000 (United Nations, 2009).

Function transfer: demand function

The DFT uses information provided by James (2003) as a case study to evaluate the viability of BT. James (2003) sought to estimate the demand for recreation at JCRP and an entrance fee as tools to support self-financing and conservation. Under the assumption of potential similarities between attributes and visitors at JCRP and OPNP, the adaptation of James (2003) demand function allows the possibility of predicting entrance fees for other regional parks in the SBR, as a new potential policy application. In this article, this process was carried out by using the estimated model from James (2003) and sample data from visitors to OPNP. A single demand function is used, under the assumption of consistent similarities between the study site (JCRP) and policy site (OPNP). The demand function for recreation at JCRP by tourists visiting San Andrés was tailored to predict a value estimate for OPNP, where such results are not available.

By using the contingent valuation (CV) method with a dichotomous choice elicitation format, James (2003) modeled the willingness to pay (WTP) as the logistic probability function below, which seeks to measure the probability of a positive answer to the WTP question. It is expressed in terms of an elicited price, country of origin, sex, age, education and employer of respondents (Table 2):

After plugging the parameters estimated by James (2003) into the above equation, the equation below is obtained. Note that only the variables of price (elicited WTP as an entrance fee to JCRP), country of origin, education and type of employer of respondents remain in the equation due to their statistical significance (price and country significant at 1%, education at 5%, and employer at 10%).

In order to transfer benefits from JCRP to OPNP, the sample mean of the independent variables measured for tourists in Old Providence and Santa Catalina (Parque Nacional Natural Old Providence McBean Lagoon, 2012) were used to calculate price using the above equation.

Function transfer: Meta-analysis

The meta-analytic BT used meta-data from Londoño and Johnston (2012), which pools together existing CV and TC studies on the recreational value of coral reefs from sites around the world. For the purpose of the analysis presented here, only CV studies from the original meta-data were selected, in order to maintain consistency of the welfare measure (Bergstrom and Taylor, 2006). The meta-data was supplemented with one observation for the SBR. The study sources include 24 original valuation studies taken from journal articles, theses, dissertations and technical reports, including one study from the SBR, namely James (2003, 2008). The list of studies in the meta-data is presented in Table 3. These studies yield a total of 71 observations (some studies provided more than one observation). Table 4 summarizes the meta-data in terms of the full set of covariates and the dependent variable, taking into account the form (linear or natural log) in which they enter the meta-regression model (MRM). Here, the WTP for a day of recreation, as a dependent variable, is hypothesized to be determined by attributes identified in the extant literature on coral reef valuation (Brander et al., 2007; Londoño and Johnston, 2012).

Table 3

Following standard procedures in the literature, the meta-analytic component was developed by implementing a multilevel model (Bateman and Jones, 2003). This corrects for cross-sectional correlation between observations from the same level (e.g. several observations from the same study), and generates more accurate measures of standard errors and significance of parameters (Goldstein, 1995; Bateman and Jones, 2003; Johnston et al., 2006). Each observation i in the meta-data is expressed through the mean WTP from study s. This is denoted by _is, which is explained by a vector of variables _is, representing the set of attributes determining the welfare measure (methodological aspects, site and population attributes), the vector of model parameters β and the error term ε_is. The effect size in the meta-regression model is denoted by:

Where u_s is the study-level random effect, which is normally distributed with E (u_s) = 0 and Var (u_s) = σ²u and e_is is an estimation level error, distributed with a zero mean and constant variance σ²e (Shrestha and Loomis, 2001). The meta-regression was estimated by using a random effects model with robust standard errors (Nelson and Kennedy, 2009).

The hypothesis of transferability was tested using an in-sample validity test, where the estimated meta-parameters are used to predict values for each observation in the sample. Here the null hypothesis implies that the difference between the meta-predicted values and the original values is zero. A t-test, as is illustrated by Shrestha and Loomis (2001), was performed.

RESULTS

The use of valuation results in policy contexts in SBR

In order to respond to the initial objective of identifying what has been valued and what insights can be gained in terms of policy uses, this section starts by analyzing valuation results in the SBR. Most of the non-market valuation studies in the SBR include recreational values of coral reefs; some of them have sought to provide value estimates that could be used to improve conservation management of coral reef services. This trend is also observed in other economic valuation studies in Colombia (Rueda et al., 2011) and around the world (Londoño-Díaz, 2010).

To the knowledge of the authors, the extant literature on non-market economic valuation applied to coral reef environments in the SBR consist of six studies, which are summarized in Table 1 in terms of: i) the valuation object, identifying both the commodity being valued and the type of value, ii) implemented valuation methods, and iii) potential policy applications from such studies. While factors i and ii are presented for basic characterization purposes, factor iii is key to the discussion of this section.

Following Laurans et al. (2013), studies in Table 1 are classified in terms of three main categories of use in policy contexts: decisive, technical, and informative. The first category refers to decisive valuations for specific decisions, implying cases in which ex-ante information on values is provided to the decision maker. Then, valuation results are used to facilitate a choice between alternatives, through tools such as benefit-cost analysis (BCA) that incorporates environmental value estimates. Newball (2001) is part of this category. From a policy perspective, results from this work supported the establishment of a MPA (Figure 1) scheme in San Andrés (established in 2005) by justifying the financial and economic rationality of the chosen protection scheme over a 20 year period. Castaño (2010) could also be placed into this category; however, it does not include a BCA. This study suggests opportunities for payments for ecosystem services (PES), based on beach management, considering the importance of this ecosystem in the financial sustainability of the SBR. Towards this purpose, the study linked beach regeneration to specific coral reef services, identifying territories to allocate conservation efforts and laying out beach management scenarios. A potential policy use from this study might involve an implementation of tourist payments for the entire SBR, pledging the resulting revenue to the maintenance of key coral reef services, conservation of organisms and beach management.

Finally, the third category corresponds to informative ecosystem services valuation to support decision making from a more broad perspective. This category relates to studies that shed light on plausible environmental policies, rather than establishing a specific alternative. Morales (1998) and Carrera (2008) provided informative results on societal preferences for environmental services. In the first case, the author sought to raise environmental awareness about landscape conservation in Old Providence. Environmental advocacy based on valuation results from this study could work to influence public policy to curb habitat transformation in Old Providence. In the second case, the author elicited the value of a coral reef conservation program in San Andrés. Findings from this study, in terms of policy options, support household participation in payments for programs to establish cultural and natural conservation mechanisms under MPA structures. Both of these studies point to monetary value estimates as a way to advocate for conservation, by informing the decision process with social preferences on ecosystem services.

Benefit transfer
Function transfer: demand function

After adapting the benefit function illustrated in the methodological section to OPNP as a policy site, the model forecasts an entrance fee of $6.5 per person. This value is higher than the weighted average of the actual entrance fee charged in 2011 ($5.1). This suggest that an entrance fee based on the results from the demand function transfer provided here could represent an increase of about 30% in total revenues for OPNP compared to the revenue based on the entrance fee charged in 2011. James (2003) does not report the standard error for of the original estimated entrance fee; this hinders the computation of a confidence interval for the adapted measure provided here.

Note also that the forecasted value is exclusively determined by socio-demographic variables in Table 2, therefore the model does not allow controlling for site differences such as the environmental quality of the local ecosystems. The MRM presented in the next section addresses that issue by incorporating coral reef cover and type of reefs as covariates within the model.

Function transfer: Meta-analysis

Results from the MRM are presented considering two aspects: i) interpretation of value surfaces with regards to theoretical expectations and statistical significance of covariates, and ii) the potential for valid meta-analytic BT. In the first case, consider the results in Table 5, which contains the statistical results of the estimated MRM. As the model was specified through a trans-log form, the coefficients in Table 5 correspond to the constant relative change in the dependent variable for a given absolute change in the value of the independent variable. Note that 6 out of the 13 covariates and the coefficient in the model are statistically significant for certain values of the dependent variable. These include four methodological covariates. Both Dichotomous choice and Payment card seem to have negative and significant relationships with WTP values, these variables are statistically are significant at p < 0.10 and at p < 0.05 respectively. These covariates, as elicitation methods, have shown similar results in the empirical literature (Rosenberg and Loomis, 2000; Stapler, 2006). Trip expenditures, as a payment vehicle, is significant at p < 0.05. This covariate, as a voluntary payment vehicle, seems to keep a positive relation with the welfare measure when compared to non-voluntary payment vehicles (e.g. entrance fees) (Brouwer et al., 1999; Campos et al., 2007; Lindhjem and Navrud, 2008). Finally, the result for Sample size suggests that observations taken from studies with larger sample sizes can result in significantly higher measures of welfare estimates (p < 0.01).

With regard to site characteristics, Table 5 indicates positive and statistically significant relationships between the welfare measure and the covariates live coral reef cover and type of reefs. The sign of these parameters is also consistent with anticipated results. However, there is no prior reference in the meta-analytic literature with respect to the significance of these covariates. The empirical evidence on the positive connection between reef quality and welfare measures has only been documented by primary studies (Parsons and Thur, 2008; Wielgus et al., 2009).

Results from the in-sample validity test indicated lower ATE compared to the results in the literature (Brander et al., 2007; Londoño and Johnston, 2012). Further research to compute out-of-sample validity testing is recommended for a closer comparison of these results to those in Brander et al. (2007) and Londoño and Johnston (2012), and when weighing the pros and cons of using MBTF for a specific policy purpose. Table 6 presents the ATE calculated from the meta-data and also the calculated TE for the SBR. As a comparative reference, Table 6 also presents the computed TE for Bonaire based on the same meta-data.

The hypothesis test of statistical equivalence of predicted and observed values was conducted through a paired t-test. This indicates that the two sets of WTP values are statistically different, implying that the TEs are statistically different from zero, which discourages the use of meta-analytic BT. Other studies conducting similar tests in different locations around the world, for both domestic and international BT, had similar findings (Shrestha and Loomis, 2001, 2003; Rosenberger and Stanley, 2006; Lindhjem and Navrud, 2008). Nevertheless, the conclusion is not straightforward for the SBR, where the individual TE for JCRP (4.5%) is smaller than the ATE (57.4%) as shown in Table 6. According to Kristofersson and Navrud (2005), reliable TEs for policy applications only need to be relatively small. Moreover, Kristofersson and Navrud (2007) suggest that a TE lower than 40% can be reliable, depending on the political application (Lindhjem and Navrud, 2008).

DISCUSSION

Existing valuation studies were analyzed with regards to policy use. But, what can be said about the actual contributions from these studies to policy making and management? The answer to this question can be partially given by the fact that three out of the seven studies in Table 1 (namely: Newball, 2001; James, 2003; Castaño, 2010) were, to some extent, performed with support from the environmental management agency of the SBR, aimed at providing results to inform timely relevant queries. In 2001, the environmental authority of the Archipelago, CORALINA, declared the JCRP. This action was followed by initiatives to conduct studies on carrying capacity of beaches and the establishment of entrance fees. As a response to this request, James (2003) provided a CV study estimating an entrance payment, which was modeled using the socio-demographic characteristics of the tourist population. In this way, the study, along with other available information, came to support the setting of an entrance fee value by the environmental authority. Newball (2001) provided an economic valuation of coral reef conservation in San Andrés, which proposed a financial model to support the implementation of an MPA in the Archipelago. Four years later, in 2005, the Seaflower MPA was declared. More recently, the topic of PES has drawn the interest of practitioners at the Seaflower MPA. As a response to that call, Castaño (2010) proposed financing mechanisms for the Seaflower MPA based on marine and coastal PES. However, the implementation of such PES projects is still in an exploratory phase in Colombia. Therefore actual contributions from this study can only be assessed in terms of the benefits of providing decision makers with ex-ante information to support a better choice of policy alternatives in the future.

International reviews on the practical benefits from valuation studies have found modest contributions from such studies. For the south Pacific, researchers found that, in general, the expected outcome for economic valuation studies was to "inform and convince" during the decision process when facing alternatives (Pascal et al., 2012). However, a difference with SBR cases remains. Generally, SBR cases do not incorporate economic comparison of alternative policies. This could be attributed to the practice of choosing policies before the economic analysis is performed. It could also be related to the perception of valuation as a tool to support policies selected through expert criteria, rather than economic criteria (e.g. efficiency, cost-efficiency, and effectiveness), or by the high cost of more comprehensive economic analyses. Pascal et al. (2012) also found that the impact of valuations on policy decisions varied, and was generally lower than expected. The authors hypothesized that such results could be a function of the time span in which results can be actually observed, i.e. the period of time could sometimes be too short to accurately quantify the effectiveness of valuation results.

In the Caribbean, a similar review (Kushner et al., 2012) also suggested that there was uncertainty on whether valuation efforts had significant impacts on policy making. However, the authors identified cases in which valuations have been influential, and outlined conditions to improve the chances that a study will be successful in influencing policy. Some conditions outlined by Kushner et al. (2012), which could be relevant for SBR, include: maintaining strong stakeholder engagement, clearly presenting methods and limitations, identifying opportunities for raising revenue, and effectively communicating with decision makers and/or media.

The case study provided by James (2003) also represents a relatively straightforward approach to evaluate the use of BT as a new policy application in the SBR. For the case of the DFT, results suggest an alternative way to provide a basis for the determination of an entrance fee in OPNP, in the absence of financial or technical resources needed to conduct a primary valuation there. Under the appropriate circumstances, BT results can be used to adjust measures initially determined ad hoc, by expert criteria or by single point value transfer (direct value transfer from another site). Demand function transfers outperform (lower error) point estimate transfers, and thus they can represent welfare improvements over point estimates (Rosenberger and Loomis, 2000). BT is, however, only a second best option. Primary valuation studies provide more accurate results, as they are based on the measurement of model parameters for visitors to the actual site, and incorporate site idiosyncrasies. For instance, the estimation of a new original model can be designed to capture site differences (e.g. mangrove presence in OPNP vs. JCRP, differences in coral reef cover, among others). BT functions may face limitations when original studies do not provide information on environmental attributes, which is the case for most studies in the SBR. With exception of Castaño (2010), environmental attributes of the study sites are not included in the valuation models for SBR, which provides a rationale for new studies. The lack of environmental attributes in the valuation model affects the capability of the model to respond to policy questions when environmental attributes change.

With regard to the viability of meta-analytic BT, the literature provides no consensus on acceptable levels of TE. However, it is generally agreed that smaller TEs are necessary when moving from simple BCA to the implementation of compensatory payments (Rosenberger and Johnston, 2009). Table 6 also reports meta-predicted values and 95% confidence intervals. For JCRP the meta-predicted value is $7.25, which represents the predicted value for an entrance fee paid by a single tourist/day. This result is comparable to others found in the CV literature in the Caribbean (Table 2), such as those in Díaz (2001) and Thur (2003). This meta-analytic result does not differ much from the one predicted by the demand function transfer for JCRP ($6.5). A higher estimate from the MRM, when compared to the demand function transfer, is associated with the set of explanatory variables used in each case. While the DFT based on James (2003) only uses socio-demographic variables, the MRM includes covariates for site (e.g. live coral cover) and methodological (e.g. elicitation format) attributes. For this situation, the meta-analytic literature has pointed out the lack of sufficient reporting of site, socio-demographic and methodological variables in primary valuation, which affects the availability of information to conduct MA (Spurgeon, 2001; Brander et al., 2007; Londoño and Johnston, 2012). For instance, the inadequate reporting of socio-demographic variables in most primary valuation studies hindered the inclusion of this set of covariates in the meta-data, and therefore the ability of the meta-regression model to assess their effect on WTP.

Overall, results indicate that valuation studies in the SBR have tended to be more in line with an informative and technical perspective than a decisive one. However this seems to be the case in other regions of the world (Kushner et al., 2012; Pascal et al., 2012). BT is a potential new policy application in the SBR, which is explored here through both DFT and MA. Findings suggest that both could represent alternatives to transfer values for the estimation of entrance fees in marine parks in the SBR. The meta-analytic version provides the additional advantage of considering the quality of the reefs as a covariate within the valuation model, which could be beneficial to assess the effect of environmental changes on estimated values. It also relaxes the assumption of close site similarities implicit in the demand function transfer by tailoring the MRM to the policy site.

CONCLUSIONS

In the SBR, like in other sites in the wider Caribbean and South Pacific regions, the connection between economic valuation results and policy design is a work in progress. The review provided here indicates two cases where studies have been influential to some extent, providing technical information to support decision making on financial sustainability of a MPA (Newball, 2001; James, 2003). The review also identified another study providing a potentially decisive evaluation, which could support the implementation of payments for coral reef services associated with beach regeneration (Castaño, 2010). Two additional cases provided informative valuations, mostly oriented towards advocacy for conservation and the promotion of environmental awareness (Morales, 1998; Carrera, 2008). The review also indicates a lack of studies providing comparative valuations of policy options before a specific policy is chosen. Although this practice is cost-saving in the short term, it can hinder the implementation of more efficient or cost-effective policies in the long term.

A value estimate was generated for OPNP using a predictive DFT, based on James (2003). This constitutes a potential new policy application based on the available studies for the SBR. The meta-analytic approach to BT indicated a low TE for the SBR, suggesting the potential use of this method when new value estimates are required, in the context of changing environmental conditions (for instance, changes in the percentage of live coral cover). However, BT options should be considered as a second best, when primary valuation is not possible.

Both the qualitative and quantitative analyses indicated the need for valuation studies that address specific, relevant policy questions. This process should be conducted with the close involvement of key stakeholders, who are the users of the valuation results. Studies in the SBR should also move beyond the economic valuation of single policy options to trade-off assessments of alternatives, prior to selection by the decision maker. The integration of more environmental attributes and socio-demographic factors into valuation models also seems necessary in order to enhance the potential for using valuation results in alternative policy contexts through more complete BT models.

ACKNOWLEDGEMENTS

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