Plant-Level, Spatial, Bioeconomic Models Of Plant Disease Diffusion And Control: Grapevine Leafroll Disease
This dissertation addresses a family of agricultural and resource problems that emerge when biophysical and economic systems are endogenously linked over space and time. In particular, we study the spatial-dynamic bioeconomics of the grapevine leafroll disease (GLRD) which threatens the economic sustainability of the grape and wine industry. The first essay of the dissertation relies on a survey with vineyard managers in the Finger Lakes region of New York to assess the economic cost of the grapevine leafroll disease and identify optimal nonspatial disease control strategies under an array of bioeconomic parameters. The second essay employs cellular automata to model the disease spatial-dynamic diffusion for individual plants in a vineyard, evaluate nonspatial and spatial control strategies, and rank them based on vineyard expected net present values. Nonspatial strategies consist of removing and replacing symptomatic grapevines. In spatial strategies, symptomatic vines are removed and replaced, and their nonsymptomatic neighbors are virus-tested, then removed and replaced if the test is positive. We find that the nonspatial strategies currently recommended to the industry are not cost-effective under model baseline parameters. In contrast, we find that spatial strategies targeting immediate neighbors of symptomatic vines increase the vineyard expected net present value by 18-19% relative to the strategy of no disease control. In the third essay, we model spatialdynamic, negative externalities generated by a plant-level disease diffusion process between two ecologically connected but independently managed, heterogonous vineyards. One vineyard produces high-value wine grapes whereas the other produces low-value wine grapes. We embed the computational model in a bargaining game between neighboring managers. We find that, under noncooperative management, it is optimal for neither manager to control the disease. Under cooperative management, we find it optimal for the high-value manager to spatially control the disease and to pay the low-value manager to do similarly. The cooperative solution increases total payoffs by 20%. Using mean-preserving price expansions and contractions, we show that total payoff decreases with the magnitude of the price differential between the neighboring vineyards up to a point where cooperation becomes Pareto-optimal and the relationship between heterogeneity and total payoff becomes U-shaped.
bioeconomic models; cellular automata; plant disease control; bargaining games; spatial-dynamic processes; externalities
Gomez, Miguel I.
Nyrop, Jan Peter; Conrad, Jon M
Ph.D. of Agricultural Economics
Doctor of Philosophy
dissertation or thesis