Spatial stochastic simulation offers potential as a quantitative method for pest risk analysis.
Pest risk analysis represents an emerging field of risk analysis that evaluates the potential risks of the introduction and establishment of plant pests into a new geographic location and then assesses the management options to reduce those potential risks. Development of new and adapted methodology is required to answer questions concerning pest risk analysis of exotic plant pests. This research describes a new method for predicting the potential establishment and spread of a plant pest into new areas using a case study, Ralstonia solanacearum, a bacterial disease of potato. This method combines current quantitative methodologies, stochastic simulation, and geographic information systems with knowledge of pest biology and environmental data to derive new information about pest establishment potential in a geographical region where a pest had not been introduced. This proposed method extends an existing methodology for matching pest characteristics with environmental conditions by modeling and simulating dissemination behavior of a pest organism. Issues related to integrating spatial variables into risk analysis models are further discussed in this article.
Rafoss
Trond
T
Department of Mathematical Sciences, Agricultural University of Norway. trond.rafoss@planteforsk.no
D017753:Ecosystem; D004783:Environmental Microbiology; D016946:Gram-Negative Aerobic Rods and Cocci / Q000302:isolation & purification / Q000472:pathogenicity; D008954:Models, Biological; D009664:Norway; D010935:Plant Diseases / Q000382:microbiology*; D012307:Risk Factors; D011198:Solanum tuberosum / Q000382:microbiology; D013269:Stochastic Processes