Natural landscapes around the world have experienced serious loss and degradation, which negatively impacts ecosystem service provision by these landscapes. As a result, there have been serious investments to restore natural capital. However, restoration faces complex trade-offs, such as that between restoration quality, or how closely the restored landscapes resembles the natural state, and quantity, or the size of restored areas, and between restoration and recreation access. It is often not clear which strategies would yield the highest social benefits for two reasons. First, most benefits arising from restoring natural landscapes are nonmarket and difficult to determine. Second, economic theoretical models tend to not account for the multi-attribute dynamic nature of habitats, which prevents them from effectively guiding restoration policy. In this dissertation, I estimate the demand for landscape restoration. I evaluate strategies to increase social benefits from restoration while meeting biological and other non-economic conservation goals. I also develop a modeling framework of dynamic investment in individual habitat attributes.
In the first manuscript, I develop and implement a choice experiment survey of public preferences for restoring sandy beach and coastal dune landscapes in the Pacific Northwest (PNW). Sandy beaches and coastal dunes in the region have been affected by invasive species to the point where they are now rare in their natural form. Respondents are asked to choose among hypothetical projects that restore portions of these landscapes so that they are closer to their natural state versus the status quo of no new restoration. In addition to project size and restoration level, defined as closeness to the natural state, restoration programs also vary by the degree of recreation access, flooding risk, and cost to households. I find that respondents prefer landscape restoration that comes close to the natural state while maintaining the same level of recreation access to the area. Annual median household willingness-to-pay for the most preferred restoration program is $65, and the greatest marginal welfare improvement is obtained by increasing quality of restoration. The results from this manuscript can help policy makers to consider public preferences when setting goals and prioritizing resources to restore a landscape.
The second manuscript builds upon the same survey to explore how familiarity affects preferences for public good. Although the PNW sandy beach and coastal dune landscapes are frequently visited, their natural state remains unfamiliar to most people as it is near nonexistent today. If restored, the landscapes would become accessible to visitors. Responses regarding recreation habits and knowledge of the landscapes are used as proxies for familiarity. Respondents aware of the changes due to invasive species are more likely to prefer restoration that is the closest to the natural state. Respondents engaging in off-road-vehicle (ORV) activity are more likely to be interested in restoration alternatives that allow ORV use within restored areas.
In the third manuscript, I develop an optimal control model to study investment in habitat for a species with non-consumptive values. Dynamics of habitat attributes, corresponding restoration strategies, and dynamics of species biomass are modelled in an ecological-economic framework. The optimal investment trajectory is solved for and compared with counterfactual policies using simulation. I examine situations in which costs of suboptimal investment are most substantial. This research integrates information regarding habitat formation in modeling the investment of natural capital.