Dealing with Heterogeneous Preferences Concerned with Lake Urmia Restoration

In recent years, most environmental valuation studies have managed the heterogeneity of preferences among individuals. Differing sensitivities are the basis for targeted communication programs and promotions. As consumer preferences and sensitivities become more diverse, it becomes less and less efficient to consider the society in the aggregate (Rossi et al. 2005). In this research, we will show how latent class approach is ideal for these problems as it is possible to produce group -level parameter estimates. Investment in the ecological health of the Great Lakes basin is pivotal to its long-term economic success (Austin et al. 2007). Lake Urmia in the northwestern corner of Iran is one of the largest permanent hyper saline lakes in the world and the largest lake in the Middle East. The lake’s surface area has been estimated to have been as large as 6100 km2 but since 1995 it has generally been declining (Eimanifar and Mohebbi, 2007) and was estimated from satellite data to be only 926 km2 in 2014 (West Azerbaijan Department of Environment, 2014). Scientists have warned that continued decline would lead to increased salinity, collapse of the lake’s food chain and ecosystem, loss of wetland habitat, windblown salt storms, alteration of local climate and serious negative impacts on local agriculture and livelihoods as well as regional health (GEAS, 2012). Worldwide Experiences indicate that sustainability of wetlands depends primarily on the extent to which local communities are active in their management. Local communities should therefore be fully engaged in the conservation and management of the Lake and its satellite wetlands. Hence, we conducted a choice experiment for investigating public preferences on the nonmarket economic benefits of Lake Urmia restoration. For environmental studies, CE has recently been applied in wetland (e.g., Westerberg et al. 2010; Dias and Belcher, 2015), water supply (e.g., Alcon et al. 2014; Justes et al. 2014;), rivers (Lizin et al. 2016; Vollmer et al. 2016) and coastal habitats (e.g., Duran et al. 2015; Marre et al. 2015).