Essays on Dynamic Optimization for Forest Resource Management

Abstract

The dissertation consists of three essays in forestry resource management, with focuses on investigating the ecosystem collapse and invasive species control problems. The first two papers consider the shift from primary forests to cleared land and secondary forests in the context of deforestation. This process is known to lead to irreversible tipping points that lead to the loss of ecosystem services. The past literature has discussed forest rotations under stochastic prices, timber volume, and amenity values. I extend this body of work to show how stochastic processes concerning primary forests could lead to ecological collapse. Drift and volatility in these processes explain different types of long-term and short-term shocks in tropical forest systems, such as fire, drought, or climate changes, all mechanisms that can drive ecosystem function to collapse. Common examples of severe ecosystem damage include the irreversible change from tropical forests to grassy savanna, fire events, and other climate problems. However, another case of uncertainty happens when ecosystem service production of primary and secondary forests itself is stochastic, so that there is a more complicated relationship between deforestation and reaching a point where ecosystem functions collapse. I compare and contrast these two cases to determine how drift and volatility determines the timing of a tipping point in a deforestation model where primary and secondary forests, as well as agricultural land, influence ecosystem function. I examine the sensitivity of the timing of collapse in both model variants to critical market and land-use parameters. The third chapter of this dissertation explores the connection between landowners' risk preferences, invasive species spread, and optimal control efforts. This study analyzes the control effort involved in neighboring infested and uninfested municipalities, which may have differing risk preferences. In the context of an application to the spread of Emerald ash borer (EAB) in the Twin Cities, Minnesota, I develop a simulation to explore the level of control and spread in a myopic policy scenario versus that in a first-best problem, where the two municipalities may be either risk neutral or risk averse. The results suggest that heterogeneity in risk aversion across the municipalities leads to lower control efforts and a longer time to drive the probability of spread to zero.