Graduate Thesis Or Dissertation
 

Optimal spatial-dynamic resource allocation facing uncertainty : integrating economics and ecology for invasive species policy

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/fb494c66v

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  • The spatial and temporal behavior of invasive species spread implies that optimal management strategies involve decisions over space and time. Dispersal and propagule pressure are two primary drivers of the spatial-temporal ecological process of species invasion. In the case of riparian communities, stream flow drives the dispersal of vegetation propagules. After arriving at a location, establishment depends in part on propagule pressure. This research incorporates an invasive species spreading through a river network over time --with stochasticity in dispersal, death, and establishment success-- into a dynamic economic decision framework to determine the optimal spatial and temporal pattern of invasive species management efforts. The optimization model employs a Markov Decision Process (MDP) solved using numerical methods. The decision framework developed in this research improves on current economic models by modeling ecological processes of invasion in an explicitly spatial setting with stochasticity to better inform the allocation of management resources. The model is parameterized to simulate the spread and management of the riparian invasive shrub, Tamarix sp., and optimal policies are applied to Monte Carlo simulations over twenty years. Several other rule of thumb policies are applied in the same way for comparison purposes. Results demonstrate that generating management plans through integrating ecology and economic tradeoffs produces management patterns that emphasize a whole-network approach rather than reach by reach; use different management tools in different locations and at different times than economic or ecological models alone; and generates substantial cost savings over other policies. The model demonstrated marked economic efficiency gains in avoided costs by optimal management that reflects the spatial and temporal processes of species invasion. In particular, results showed that simplifications of the ecology that ignores low probability dispersal events lead to costly misspecification of management tool, location and timing. Overall, the integration of key ecological characteristics into a stochastic, spatio-dynamic economic optimization considering the state of the entire river network avoids large errors in the management tool, its location, and its timing that simpler frameworks prescribe.
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