Graduate Thesis Or Dissertation
 

Spatial heterogeneity, meta-analysis and spatial dependence : three essays on environmental valuation and spatial land management decisions

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/x633f327b

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  • This dissertation consists of three essays that collectively address the importance of accounting for spatial heterogeneity and spatial dependence of environmental assets and natural resources in policy making. The first essay examines the value of different wetland ecosystem services using an expanded meta-dataset of valuation studies in North America. The purpose of this essay is to explore the sources of variation in wetland values from valuation methodology, ecosystem functions, and site-specific geographic, demographic and socio-economic characteristics. This essay used panel random effect models stratified "by study", "by state" and "by wetland site" to address the issues of correlation between wetland value estimates. Results indicated that wetland welfare measures reported by the same study and in the same wetland site are correlated. By comparing regression results and conclusions from this study with two internationally scoped meta-analysis studies, this essay found that the wetland valuation literature is not robust to regional characteristics, and wetland welfare estimates are sensitive to geographic extent. The second essay extends the first essay to investigate spatial spillover effects of wetland welfare estimates in North America. The primary purpose of the essay is to explore whether wetland values are correlated across space and what determines the correlation. The goal is accomplished by incorporating spatial econometric methods into the meta-analysis framework. The essay constructed three spatial weight matrices based on threshold distances, the ecological similarity and the economic similarity of wetland sites in the metadata. Results indicate that spatial proximity is an important predictor of wetland values regardless of wetland type and function. In part this is captured through shared contexts including resource availability and market characteristics. However, similar ecological and economic profiles are insufficient to capture shared values when transferring value estimates across spatial areas. Results from this study also raised questions on whether ecological functions and economic markets are sufficient for improving international transfers when studies are beyond geographic thresholds. The third essay incorporates spatial econometric models into a stochastic optimization framework to explore the consequences of ignoring the spatial linkage of management units in land management outcomes. The integrated framework combines an economic decision model, a spatial fire simulation model, a spotted owl population prediction model to maximize the expected post-fire and post-treatment NSO population under a budget constraint. Results from this essay inform us that ignoring spatial habitat connections leads to an underestimate of the fuel treatment disturbance and an over-estimate of the expected post-fire and post-treatment NSO population. However, the negative externality of habitat conversions depends on the degree of habitat connections. Additionally, the amount of total treatment area depends on the degree of habitat connections. The optimization outcome suggests less fuel treatment for a landscape with a higher degree of habitat connections. Moreover, the optimization outcome informs us that the spatial configuration of fuel treatment matters for the NSO population protection. Ignoring the spatial habitat connections leads to a fragmented treatment pattern and fails to protect the core NSO habitat from treatment disturbances.
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