Estimating the spatial dispersion of pest arthropods is crucial for the development of reliable sampling programs and one of the main components of integrated pest management. The natural spatial distribution of a population of a species may be random, uniform, or aggregated and can be so classified based on calculation of variance to mean relations and related dispersion indices. In this work some classical density-invariant dispersion indices and related regression models are used for the first time to quantify the spatial dispersion of an important peach pest Anarsia lineatella Zeller (Lepidoptera: Gelechiidae) and construct fixed precision sequential sampling schemes. Taylor's power law, Iwao's patchiness regression and Nachman's model were used to analyse the damage to peaches caused by A. lineatella. All three regression models fit the data well, although the results indicate that Iwao's patchiness model provides a better description of the relationship between variance and mean density. Taylor's b and Iwao's b regression indices were both significantly smaller than 1, indicating that the distribution of individuals was uniform rather than random or aggregated. According to Green's and Kuno's models, the minimum sample size at the precision level of 0.2 varies from 3 samples, when total population density is more than 3 larvae/sample, to 10 samples, when population density is between 1 and 2 larvae/sample. Kuno's fixed sampling plan indicates that a small number of samples (i.e., 3-10 branches with fruit) is sufficient to estimate the mean population density of A. lineatella larvae with a precision of 0.2. The Resampling for validation of sampling plans (RVSP) method confirmed that the average level of precision of the fixed sequential plans matched the desired precision in most cases. The sampling plan presented here provides a level understanding of A. lineatella spatial ecology suitable for pest manage, Petros Damos., and Obsahuje bibliografii