Interpreting Data from Trapping of Stochastic Movers

数学物理学家Jeff Schenker教授和昆虫学家James米勒教授之间的合作旨在对昆虫诱捕科学，特别是农业害虫的基本理解。 在用诱饵（通常是信息素）诱捕的陷阱中捕获单个昆虫长期以来一直是田间生物学中的关键测量技术。 陷阱中捕获的个体数量可以揭示哪些昆虫存在以及它们何时活动。 然而，将捕获的数量转化为对害虫密度（在给定区域发现的害虫数量）的准确估计的困难问题目前知之甚少。 该项目旨在通过野外实验，计算机模拟和理论研究相结合来解决这个问题，以接近昆虫飞行的随机运动。 更好地了解诱捕将有助于农业害虫管理人员，在入侵物种的检测和管理，并在监测和控制昆虫疾病传播媒介。 特别是，针对种群估计的改进对农民来说将是一个布恩，只有当有明确的科学证据表明施用成本被种植者的潜在损失所抵消时，虫害管理人员才能推荐杀虫剂喷雾等干预措施。这项工作将遵循一个综合方案的数学研究竞争性诱捕随机移动和现场实验的显着释放/捕获的昆虫。 目的是回答两个问题：（1）给定一系列的几个陷阱什么信息的传播，流动性和人口密度可以推断出从各种渔获量？(2)鉴于几个陷阱，我们如何才能最好地安排他们准确地推断估计人口密度的渔获量数据？ 在过去，关于这两个问题的一个缺失环节一直是捕获概率的准确表示，因为它随着动物从陷阱起源的距离而变化。 研究人员已经取得了相当大的进展，利用计算机模拟的随机步行者模型捕获。 通过对扩散和随机游走进行数学分析和数值研究，研究小组预计能够从该领域容易且廉价收集的数据中提取重要的科学测量结果。

This collaboration between mathematical physicist Prof. Jeff Schenker and entomologist Prof. James Miller aims at a fundamental understanding of the science of trapping of insects, particularly agricultural pests. Capture of individual insects in traps baited with a lure, often a pheromone, has long been a critical measurement technique in field biology. The number of individuals caught in a trap can reveal which insects are present and when they active. However, the difficult problem of converting the number captured into an accurate estimate of pest density (the number of pests to be found in a given region) is at present poorly understood. This project aims to solve that problem through a combination of field experiments, computer simulations, and theoretical investigations into random movements that approximate insect flight. Better understanding of trapping will be of use to agricultural pest managers, in the detection and management of invasive species, and in monitoring and controlling the spread of insect disease vectors. In particular, the aimed-for improvements in population estimation will be a boon for farmers, allowing pest managers to recommend interventions like insecticide sprays only when there is clear scientific evidence that the cost of application is offset by the potential loss to the grower. The work will follow an integrated program of mathematical investigations on competitive trapping of stochastic movers and field experiments of marked release/capture of insects. The aim is to answer two questions: (1) Given an array of several traps what information about the dispersal, mobility and population density may be inferred from the various catches? (2) Given several traps how may we best arrange them to accurately infer estimates on population density from catch data? In the past, a missing link in regards to both problems has been an accurate representation of the probability of catch as it varies with the distances animals originated from the trap. The investigators have made considerable progress on modeling catch using computer simulated random walkers. By bringing mathematical analysis and numerical study of diffusion and random walks to bear on the problem, the research team anticipates being able to extract important scientific measurements from data that can be gathered easily and inexpensively in the field.