Sampling in precision IPM: When the objective is a map

Abstract

Measuring and understanding spatial variation of pests is a fundamental component of population dynamics. The resulting maps can drive spatially variable pest management, which we define as precision integrated pest management (IPM). Precision IPM has the potential to reduce insecticide use and slow the rate of resistance development because of the creation of temporally dynamic refuges. This approach to IPM requires sampling in which the objective is to measure spatial variation and map pest density or pressure. Interpolation of spatially referenced data is reviewed, and the influence of sampling design is suggested to be critical to the mapped visualization. Spatial sampling created problems with poor precision and small sample sizes that were partially alleviated with choosing sampling units based on their geostatistical properties, adopting global positioning system technology, and mapping local means. Mapping the probability of exceeding a threshold with indicator kriging is discussed as a decision-making tool for precision IPM. The different types of sampling patterns to deploy are discussed relative to the pest mapping objective.