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There is rich literature in reserve site selection for wildlife conservation, but little has investigated the spatial correlation of risks presented by hazards. This paper contributes to the literature by applying the modeling framework developed in Busby et al. (2011), which incorporates spatially correlated risk into the reserve site selection problem, to a Virginia landscape where fine-scale species data is available. In this context, we consider both homogeneous and heterogeneous on-site land development risks. Finally, we apply a budget constraint to our maximal covering species problem to investigate how land cost impacts optimal reserve design and the level of species protection. Using fine-scale species data in the analysis, we identify the types of settings where incorporating spatially correlated risk into conservation reserve design can lead to significant improvements in species protection.

Across the U.S., wildfires have become increasingly destructive and costly over the past few decades, with impacts particularly severe in the State of Florida. Because of an increase in wildfire frequency and severity and the number of people living in fire-prone areas the issue of wildfire risk management is of growing significance. One of the most important wildfire risk reduction tools is prescribed fire to reduce fuel loads, thereby reducing wildfire intensity and resulting damages. Because fire moves across a landscape and ownership boundaries, the spatial pattern of fuel load reduction may influence individual landowners' decisions about fire risk management on their own property. We develop and empirically test a spatial econometric model to study the interaction between Florida landowners in their wildfire risk management decisions. Master of Science

As more emphasis is put on biodiversity conservation, how best to select a system of protected areas for wildlife conservation is an issue of great importance. There is a rich economics literature on the reserve site selection problem. However, most economic studies assume the independence of risks that affect wildlife species, leaving the issue of spatially correlated risk largely unexplored. This study contributes to the literature in twoaspects. First, this study incorporates spatially correlated risk, into a reserve site selection model. And second, this study incorporates heterogeneous spatial risk, in the context of land development risk in Virginia, both with and without a budget constraint. To evaluate the significance of spatially correlated risk in conservation design, I apply the reserve site selection model to a Virginia landscape. In a basic setting, a hazard is introduced which is allowed to spread to adjacent land parcels, where I investigate the impact of spatially correlated risk at three spatial scales: one-county, four-county, and state-level. Optimal reserve designs are characterized by similar spatial patterns indicating that spatially correlated risk plays an important role in the selection of parcels for reserve. Specifically, as spatially correlated risk increases, I find that, in general, reserve connectivity decreases. I also examine a setting with heterogeneous risk and observe similar patterns in the optimal reserve design. I find that the reserve becomes more dispersed in higher risk areas primarily. Finally, I explore the tradeoffs between species protection and budget constraints in the presence of heterogeneous spatial risk. All comparative statics indicate that spatial correlated risk plays an important role in conservation reserve design. Master of Science

In this dissertation, we study the effects of emerging biomass markets on land use changes between alternatives of agricultural production, conventional timber production, and forest woody biomass production for energy use. Along with the uncertainty associated with woody biomass prices and rents, transaction costs incurred to land use play an important role in land allocation decisions and make this study distinct from other work. In Chapter 1, we introduce the background and objectives of our study. In Chapter 2, we analyze the behavior of a risk-neutral private landowner and social planner under uncertainty of woody biomass prices, assuming that there is a market emergence at some unknown time point in the future. Market emergence is characterized by a price jump and a certain timing of the price jump. Six different price jumps and five different timings of bioenergy market emergence are adopted to study their collective effects on land use change between agriculture and forestry. Chapter 3 studies this problem for a risk-averse private landowner. Two measures of relative risk aversion are used to examine how a landowner's preference may affect his or her land use decision. In Chapter 2, we find that, for three different quality categories of land, land rents from forestry increase significantly for higher price jumps and decreases in the length of time until bioenergy market emergence. One of the most important results is concerned with the presence of transaction costs. Here, we find that these costs may require unrealistic market emergence scenarios to lead to bioenergy adoption on any large scale. This result is even more likely with nonlinear transaction costs. Land allocation decisions in Chapter 3 are distinctly different from those in Chapter 2, due to the introduction of landowner risk aversion. In certain market emergence cases, some land units retain in agriculture entirely when the landowner is risk averse . The Chapter 4 studies a stochastic optimization problem of land use, assuming that woody biomass rents follow a stochastic diffusion called geometric Brownian motion that is later discretized by a binomial option pricing approach. The problems in Chapters 2 and 3 assume that the landowner must make all decisions at the beginning of his or her time horizon. This assumption is relaxed in Chapter 4. Now, the landowner is allowed to revise his or her land allocation decision among three alternatives over time as information about market emergence is collected. We observe that the different forms of transaction costs are not as significant as in Chapters 2 and 3. However, different values of volatility of forest biomass rents give rise to different land allocation decisions, especially for the land of high quality. Ph. D.