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Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker’s?perspective

机译:量化有害生物风险图和评估中的不确定性:采用规避风险的决策者的观点

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Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker. We demonstrated the approach by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new approach offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decision-making preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada.
机译:在设计策略以最大程度地减少入侵生物的引入并减轻其影响时,害虫风险图是重要的决策支持工具。当管理层对入侵者的可能应对措施包括代价高昂或对社会敏感的活动时,决策者往往会采取更加确定的(即规避风险)措施。我们提出了一种新的映射技术,可以从规避风险的决策者的角度评估害虫入侵的风险。我们通过评估入侵性森林有害生物被来访美国联邦营地的游客将木柴转移到美国一个州或加拿大各省之一的可能性来证明了这种方法。我们使用根据地理记录模型确定的有害生物到达情景的分布测试了风险规避假设的影响,该情景是通过记录营员在整个研究区域旅行的数据开发的地理显式模型得出的。接下来,我们通过应用分别采用第一级和第二级随机优势规则的两种随机排序技术,对高和低有害生物到达风险区域进行了优先排序,后者采用了风险规避概念。然后,我们在研究区域中确定了在引入风险规避之后有害生物风险值发生了很大变化的区域。虽然这两种方法都确定了最高和最低风险的相似区域,但它们在划分中度风险区域的方式上却有所不同。通常,二阶随机优势方法将较低的风险等级分配给中度风险区域。总体而言,这种新方法提供了一种更好的策略来处理通常与风险评估相关的不确定性,并提供了一种将决策偏好纳入最终风险估算的简便方法,从而有助于将这些估算与以下特定决策场景更好地保持一致:有害生物。并入风险规避还有助于确定一组位置,将其定位为检查和外展活动的目标,这可能会导致成本高昂。鉴于美国和加拿大每年都有大量的露营旅行,因此我们的结果特别重要和有用。

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