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Spatial Stochastic Simulation Offers Potential as a Quantitative Method for Pest Risk Analysis

机译:空间随机模拟提供了潜在的病虫害风险分析方法

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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.
机译:病虫害风险分析是风险分析的一个新兴领域,该领域评估将植物害虫引入和定植到新地理位置的潜在风险,然后评估减少这些潜在风险的管理方案。需要开发新的适应性方法来回答有关外来植物有害生物风险分析的问题。这项研究描述了一种新的方法,该方法使用案例研究Ralstonia solanacearum(马铃薯的一种细菌性疾病)来预测植物有害生物的建立和传播。该方法将当前的定量方法,随机模拟和地理信息系统与有害生物生物学和环境数据相结合,以得出有关尚未引入有害生物的地理区域中有害生物形成潜力的新信息。该提议的方法扩展了现有的方法,通过建模和模拟有害生物的传播行为,使有害生物特性与环境条件相匹配。本文将进一步讨论与将空间变量集成到风险分析模型中有关的问题。

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