Community values for environmental protection in a cane farming catchment in northern Australia: a choice modelling study

Choice modelling is an emerging approach to estimating the non-use values of environmental services with multiple attributes. In this paper, results are reported of a choice modelling study conducted in the Herbert River District of North Queensland to estimate the value placed on the protection of natural vegetation in areas suitable for cane production by the local community. Resource use options that vary in the level of environmental protection and the level of agricultural production were presented as a series of choice sets and respondents were asked to choose among a set of three discrete alternatives in a given choice set. The alternatives in each choice set were described by four attributes, pertaining to the area of teatree woodlands, the area of vegetation along rivers and in wetlands, regional income from cane production, and an environmental levy. The responses were analysed together with socio-economic data using a nested-logit discrete-choice model to estimate the community willingness-to-pay for the protection of natural vegetation. The results indicate that the environmental values of wetlands are comparable to returns from commercial production of sugar cane and that the values of teatree woodlands are comparable to returns from extensive grazing. It is argued that land allocation policies should recognise these values in tandem with commercial benefits of production to ensure that resources are used more efficiently.     

Using local knowledge to model asymmetric preference formation in willingness to pay for environmental services

This paper describes an approach to account for asymmetric preference formation in discrete choice models used for environmental valuation. The paper draws on data from a case study on preferences for environmental change resulting from a hypothetical rural development and conservation programme in Indonesia. Local knowledge on the current state of the environment was used to define an individual-specific status quo that consistently frames changes in a range of environmental services as gains or losses matching the perceptions of the local population living in the vicinity of a National Park. I estimated choice models that included separate parameters for increases and decreases in attribute levels for the environmental services and derived the indicators of local willingness to pay (WTP) corresponding to the bidirectional changes relative to the individual-specific status quo option. I found clear evidence of an asymmetric response to increase and decrease in attribute levels relative to the status quo. Ignoring asymmetric preference formation can therefore result in biased estimates of WTP indicators and welfare measures of change in cases where the outcomes of environmental programmes can plausibly result in both an increase and a decrease relative to a reference option. Compared to a symmetrical modelling approach, the combination of simultaneously accounting for asymmetric preference formation and preference heterogeneity in the choice model yielded additional insights that may be used to inform the development of local strategies towards biodiversity conservation.     

Scenario realism and welfare estimates in choice experiments--a non-market valuation study on the European water framework directive

Using choice experiment data for economic valuation we analyse how disbelief in survey information could affect the retrieved welfare estimates. We distinguish between two types of survey information to the respondents. The first type of information concerns the current environmental status of a water body. This information is provided prior to the valuation questions and the corresponding beliefs in the provided information are also elicited before valuation. The second type of information concerns the proposed improvements in the environmental status of the water body. We find that average welfare measures differ considerably according to whether respondents who disagree with the status quo levels and find proposed scenarios unlikely are included or not.     

Residents' willingness to pay for improved liquid waste treatment in urban Ethiopia: results of choice experiment in Addis Ababa

This paper discusses residents’ willingness to pay (WTP) for improved liquid waste treatment in Addis Ababa based on data collected in 2011 using random parameter logit model. Findings indicate that respondents are willing to contribute for improved liquid waste treatment with higher quantity and quality. Their mean WTP for the medium improvement scenario is found to be 15.53 ETB (0.93 USD) per month. The compensation surplus tends to increase from the status quo to the alternative scenarios with aggressive improvement. Finally, the paper concludes by indicating the socioeconomic difference across households, and sub-cities need to be considered in designing environmental protection plans for the city.     

An Exploration of Dynamical Systems Modelling as a Decision Tool for Environmental Policy

A weakness often found in conventional environmental management tools is that of treating the dynamics of environmental effects and the underlying dynamics of structural change as external factors, precluding their ability to capture the evolutionary behaviour which characterizes economic systems. This article suggests a spatial dynamic modelling framework which addresses explicitly complex sectorial linkages and their environmental effects. The economic dynamics of the model are given spatial reference by means of a set of sector-based suitabilities, which allows us to explore both local environmental degradation effects as they unfold, and how these impacts then affect the economic productivity of the system as a whole. The approach is illustrated by calibrating the model with 1971-1981 data for the island of Crete, and then running it to explore how the economic dynamics of the island might evolve to the year 2001. This article presents a means through which to endogenize the environment and its explicit linkages with sectorial economic dynamics which can be of considerable use to environmental management in all its dimensions.     

Revisiting a statistical shortcoming when fitting the Langmuir model to sorption data

The Langmuir model is commonly used for describing the sorption behavior of reactive solutes to surfaces and is often fit to sorption data using nonlinear least squares regression. An important assumption of least squares regression is that the predictor variable is error free. In the case of sorption data, this assumption is not valid, and therefore the potential for parameter bias exists. Although alternative regression methods exist that either explicitly account for error in the predictor variable (Model II regression) or minimize the error in the predictor variable, these methods are not commonly used. Therefore, this paper more fully explores the differences in fitted parameters and model fits between these different data fitting methods by fitting P sorption data collected on 26 different soil samples using three different regression methods. For a majority of soils tested in this study, the differences in model fits between the three regression methods were not statistically significant. Statistical differences were observed in over a third of the soils, however, suggesting that errors in the predictor variable may be large enough to produce biased parameter estimates. These results suggest that multiple regression methods should be used when fitting the Langmuir model to sorption data to better assess the potential impact of error on model fits.     

Improving National-Scale Carbon Stock Inventories Using Knowledge on Land Use History

National-scale inventories of soil organic carbon (SOC) and forest floor carbon (FFC) stocks have a high uncertainty. Inventories are often based on the interpolation of sampled information, often using a number of covariables to help such interpolation. The rationale for the choice of these covariables is not always documented, despite the fact that many local-scale studies have identified the factors explaining spatial variability of SOC and FFC stocks. These studies indicate, among others the importance of long-term land use history. Despite this, information on the effects of land use history has never been used to explain variability of carbon stocks in national-scale inventories. We designed an alternative method to improve national-scale inventories of SOC and FCC for the Dutch sand area that takes stock of the findings of detailed case studies. Determinants for SOC and FFC stocks derived from landscape-scale case studies were used to map national-scale spatial variability and to calculate national totals. The resulting national-scale spatial distribution was compared with the SOC stock map from the current Dutch greenhouse gas inventory. Using land use history to explain SOC variability decreased the error of the SOC stock estimate in 60 % of the area. The error in FFC stocks decreased in half of the forest area after including soil fertility, tree species, and forest age as explanatory factors. Estimates with reduced uncertainty will make land use and land management a more attractive and acceptable mitigation option to reduce emissions of greenhouse gases for the LULUCF sector.     

Life cycle assessment of waste paper management: The importance of technology data and system boundaries in assessing recycling and incineration

The significance of technical data, as well as the significance of system boundary choices, when modelling the environmental impact from recycling and incineration of waste paper has been studied by a life cycle assessment focusing on global warming potentials. The consequence of choosing a specific set of data for the reprocessing technology, the virgin paper manufacturing technology and the incineration technology, as well as the importance of the recycling rate was studied. Furthermore, the system was expanded to include forestry and to include fossil fuel energy substitution from saved biomass, in order to study the importance of the system boundary choices. For recycling, the choice of virgin paper manufacturing data is most important, but the results show that also the impacts from the reprocessing technologies fluctuate greatly. For the overall results the choice of the technology data is of importance when comparing recycling including virgin paper substitution with incineration including energy substitution. Combining an environmentally high or low performing recycling technology with an environmentally high or low performing incineration technology can give quite different results. The modelling showed that recycling of paper, from a life cycle point of view, is environmentally equal or better than incineration with energy recovery only when the recycling technology is at a high environmental performance level. However, the modelling also showed that expanding the system to include substitution of fossil fuel energy by production of energy from the saved biomass associated with recycling will give a completely different result. In this case recycling is always more beneficial than incineration, thus increased recycling is desirable. Expanding the system to include forestry was shown to have a minor effect on the results. As assessments are often performed with a set choice of data and a set recycling rate, it is questionable how useful the results from this kind of LCA are for a policy maker. The high significance of the system boundary choices stresses the importance of scientific discussion on how to best address system analysis of recycling, for paper and other recyclable materials.     

Life cycle assessment of waste paper management: The importance of technology data and system boundaries in assessing recycling and incineration

The significance of technical data, as well as the significance of system boundary choices, when modelling the environmental impact from recycling and incineration of waste paper has been studied by a life cycle assessment focusing on global warming potentials. The consequence of choosing a specific set of data for the reprocessing technology, the virgin paper manufacturing technology and the incineration technology, as well as the importance of the recycling rate was studied. Furthermore, the system was expanded to include forestry and to include fossil fuel energy substitution from saved biomass, in order to study the importance of the system boundary choices. For recycling, the choice of virgin paper manufacturing data is most important, but the results show that also the impacts from the reprocessing technologies fluctuate greatly. For the overall results the choice of the technology data is of importance when comparing recycling including virgin paper substitution with incineration including energy substitution. Combining an environmentally high or low performing recycling technology with an environmentally high or low performing incineration technology can give quite different results. The modelling showed that recycling of paper, from a life cycle point of view, is environmentally equal or better than incineration with energy recovery only when the recycling technology is at a high environmental performance level. However, the modelling also showed that expanding the system to include substitution of fossil fuel energy by production of energy from the saved biomass associated with recycling will give a completely different result. In this case recycling is always more beneficial than incineration, thus increased recycling is desirable. Expanding the system to include forestry was shown to have a minor effect on the results. As assessments are often performed with a set choice of data and a set recycling rate, it is questionable how useful the results from this kind of LCA are for a policy maker. The high significance of the system boundary choices stresses the importance of scientific discussion on how to best address system analysis of recycling, for paper and other recyclable materials.     

‘Been There Done That’: Disentangling Option Value Effects from User Heterogeneity When Valuing Natural Resources with a Use Component

Endogeneity bias arises in contingent valuation studies when the error term in the willingness to pay (WTP) equation is correlated with explanatory variables because observable and unobservable characteristics of the respondents affect both their WTP and the value of those variables. We correct for the endogeneity of variables that capture previous experience with the resource valued, humpback whales, and with the geographic area of study. We consider several endogenous behavioral variables. Therefore, we apply a multivariate Probit approach to jointly model them with WTP. In this case, correcting for endogeneity increases econometric efficiency and substantially corrects the bias affecting the estimated coefficients of the experience variables, by isolating the decreasing effect on option value caused by having already experienced the resource. Stark differences are unveiled between the marginal effects on WTP of previous experience of the resource in an alternative location versus experience in the location studied, Newfoundland and Labrador (Canada).     

The effect of experience on choosing where to go: an application to a choice experiment on forest recreation

The main objective of this paper is to investigate the impact of experience on the choice of visits to forests in a stated discrete choice experiment. Recent literature has indicated that experiences with the environmental services valuated may increase the respondents' certainty in their choice of hypothetical alternatives. We apply two indicators of experiences: the number of visits and the number of different forests visited during the last year. Applying the generalized multinomial logit model, we find that an increase in the number of visits to forests makes respondents' choices more predictable. However, the number of different forests visited reduces the predictability of choices. Furthermore, we investigate the relationship between respondents' experience of forest recreation and the self-reported choice certainty, controlling for respondents' social-demographics and other design characteristics. Finally, we show that self-reported choice certainty is positive correlated with the scale factor, as expected.     

Linking linear programming and spatial simulation models to predict landscape effects of forest management alternatives

Forest management planners require analytical tools to assess the effects of alternative strategies on the sometimes disparate benefits from forests such as timber production and wildlife habitat. We assessed the spatial patterns of alternative management strategies by linking two models that were developed for different purposes. We used a linear programming model (Spectrum) to optimize timber harvest schedules, then a simulation model (HARVEST) to project those schedules in a spatially explicit way and produce maps from which the spatial pattern of habitat could be calculated. We demonstrated the power of this approach by evaluating alternative plans developed for a national forest plan revision in Wisconsin, USA. The amount of forest interior habitat was inversely related to the amount of timber cut, and increased under the alternatives compared to the current plan. The amount of edge habitat was positively related to the amount of timber cut, and increased under all alternatives. The amount of mature northern hardwood interior and edge habitat increased for all alternatives, but mature pine habitat area varied. Mature age classes of all forest types increased, and young classes decreased under all alternatives. The average size of patches (defined by age class) generally decreased. These results are consistent with the design goals of each of the alternatives, but reveal that the spatial differences among the alternatives are modest. These complementary models are valuable for quantifying and comparing the spatial effects of alternative management strategies.     

Estimating irrigation water demand in the Moroccan Drâa Valley using contingent valuation

Irrigation water management is crucial for agricultural production and livelihood security in Morocco as in many other parts of the world. For the implementation of an effective water management, knowledge about farmers' demand for irrigation water is crucial to assess reactions to water pricing policy, to establish a cost-benefit analysis of water supply investments or to determine the optimal water allocation between different users. Previously used econometric methods providing this information often have prohibitive data requirements. In this paper, the Contingent Valuation Method (CVM) is adjusted to derive a demand function for irrigation water along farmers' willingness to pay for one additional unit of surface water or groundwater. An application in the Middle Draa Valley in Morocco shows that the method provides reasonable results in an environment with limited data availability. For analysing the censored survey data, the Least Absolute Deviation estimator was found to be a more suitable alternative to the Tobit model as errors are heteroscedastic and non-normally distributed. The adjusted CVM to derive demand functions is especially attractive for water scarce countries under limited data availability.     

Nutrient-Balance Modeling as a Tool for Environmental Management in Aquaculture: The Case of Trout Farming in France

The control and prevention of nutrient pollution from fish farming plays an essential role in the French regulatory framework. Assessing nutrient emissions from fish farms is important in terms of farm authorization, taxation, and monitoring. Currently employed strategies involve both water sampling and empirical modeling. This article reports the work and outcomes of an expert panel that evaluated existing methodologies and their possible alternatives. The development and evaluation of a nutrient-balance approach was assessed as a potential alternative to currently used methodologies. A previously described nutrient-balance model was suggested and parameterized using expert choice, and its validity and applicability were assessed. The results stress that the nutrient-balance model provides more robust and relatively conservative waste estimates compared to the currently used methodologies. Sensitivity of the approach to the uneven data quality available at farm level, difficulties of on-farm measurements, as well as model requirements and limitations are discussed.     

Evaluating the Impacts of Environmental Flow Alternatives on Reservoir and Recreational Operations Using System Dynamics Modeling

Providing environmental flows is increasingly a management obligation in many water resource systems. Evaluating the impacts of environmental flow alternatives on other water uses in a basin can be a challenge, especially when collaborating with stakeholders. We demonstrate the use of system dynamics (SD) modeling to assess the impacts of four environmental flow alternatives in the Rio Chama, New Mexico. The model was developed to examine impacts of each alternative on reservoir storage and releases, hydropower production and revenue, and whitewater boating access. We simulated each alternative within a stochastic framework in order to explicitly incorporate hydrologic uncertainty into the analyses. The environmental flow alternatives were developed at a collaborative workshop of geomorphology, hydrology, and ecology experts. Results from the model indicate that the proposed flow recommendations on the Rio Chama will generally decrease annual reservoir storage, increase median flows, and have minimal impacts on hydropower production and whitewater rafting on the system. The Rio Chama case study is a promising example of how SD modeling can be used in the early stages of environmental flow studies and why it is compatible with collaborative modeling.     

Using triple bottom line metrics and multi-criteria methodology in corporate settings

With the growing importance of environmental sustainability in the corporate sector, businesses are compelled to progress from assessing and benchmarking their environmental impact to making decisions on how to prioritize impact reduction alternatives. Most often, business decisions are driven by financial metrics, but with sustainability improvements becoming a business goal, it is also important to assess metrics from environmental and social spheres; nevertheless, practically and systematically performing such an assessment is challenging. We present an application of a multi-criteria decision analysis (MCDA) method that addresses the aforementioned challenges in a corporate setting. Our case study company – one of the largest inland marine freight carriers in the United States – promotes a business culture focused on financially viable, yet socially and environmentally responsible solutions. Thus, we combine life cycle analysis (LCA), financial calculation methods, and corporate surveys to quantify environmental, economic, and social performance measures, respectively. Multiattribute utility theory is integrated with analytic hierarchy processes (AHPs) and fuzzy analysis to create a carefully designed framework for corporations with diverse groups of stakeholders. With company leadership, implementation is feasible and successful at prioritizing alternatives among diverse stakeholders. The process provides a platform for negotiation and promotes discussions on decision drivers. The use of MCDA methodologies promoted the inclusion of a suite of metrics that aligned with the company's sense of social and environmental responsibility, generating an in-depth analysis of the alternatives that factored in other things besides economics. Return-on-investments (ROI) calculations, the typical approach used in the corporate setting, would have required significantly less time and effort from the company, but the results of our MCDA application indicated that inclusion of triple bottom line metrics delve deeper into stakeholder preferences. Thus, our case study company gained a holistic view of the candidate alternatives, in addition to creating a platform for structured discussions about company goals and priorities.     

MULTI-CRITERION RANKING OF ALTERNATIVE LONG-RANGE WATER RESOURCE SYSTEMS1

ABSTRACT The definition and comparison of alternative water resource systems designed to meet long-range goals (say 60 years) is illustrated by a case study in Hungary. A comprehensive cost-effectiveness approach is adapted to define goals, specifications, criteria, alternatives and their capabilities. Specifications include demands given in probabilistic terms. The comparison of alternative systems is based on 12 criteria, one of which is the balance between total energy consumed and peak energy produced. Important factors involving social elements, such as flood protection and land and forest use, are described both as monetary quantities and as qualitative appreciations. Five alternative systems are defied involving flat land reservoirs, pumped storage reservoirs, interbasin transfer, and conjunctive use of surface and ground water. International cooperation is then used to rank systems and reduce the problem to a tradeoff between only two alternatives.     

Bringing diverse knowledge sources together--a meta-model for supporting integrated catchment management

Integrated catchment management (ICM), as promoted by recent legislation such as the European Water Framework Directive, presents difficult challenges to planners and decision-makers. To support decision-making in the face of high complexity and uncertainty, tools are required that can integrate the evidence base required to evaluate alternative management scenarios and promote communication and social learning. In this paper we present a pragmatic approach for developing an integrated decision-support tool, where the available sources of information are very diverse and a tight model coupling is not possible. In the first instance, a loosely coupled model is developed which includes numerical sub-models and knowledge-based sub-models. However, such a model is not easy for decision-makers and stakeholders to operate without modelling skills. Therefore, we derive from it a meta-model based on a Bayesian Network approach which is a decision-support tool tailored to the needs of the decision-makers and is fast and easy to operate. The meta-model can be derived at different levels of detail and complexity according to the requirements of the decision-makers. In our case, the meta-model was designed for high-level decision-makers to explore conflicts and synergies between management actions at the catchment scale. As prediction uncertainties are propagated and explicitly represented in the model outcomes, important knowledge gaps can be identified and an evidence base for robust decision-making is provided. The framework seeks to promote the development of modelling tools that can support ICM both by providing an integrated scientific evidence base and by facilitating communication and learning processes.     

Assessing visitor satisfaction with tourism rejuvenation policies: the case of Rimini,Italy

This paper assesses the appeal of potential interventions on the tourism offer of Rimini, a popular Italian seaside holiday destination, by means of a choice modelling analysis. Tourism can be viewed as a composite good, its overall utility depending on the arrangement of the component characteristics. The discrete choice experiments here incorporate as attributes a number of possible changes to current tourist activities (the subject of public debate), including them in hypothetical alternative holiday packages. The conditional logit analysis indicates that tourists show lesser preference for interventions aimed at protecting the environmental integrity of the beach and greater preference for those, such as the creation of a pedestrianised seafront with late-night opening of amenities and facilities, that are likely to diminish the role of the traditional sea, sun and sand component of the overall holiday experience.