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To address the new challenge of bringing more nature into the urban environment and developing adequate green infrastructure management methods, it is necessary to clarify the regularities of the distribution of the main ecosystem components—soil organism communities on the urban gradient. Microarthropods—collembolans and mites—are the most diverse soil animals and bioindicators of soil conditions. However, no suitable approaches exist so far to help reduce the high workload of soil zoological studies and make the data acquisition for soil assessment faster. To get closer to a solution to this problem, we propose a robust sampling approach using one pooled sample per site with surface area 58 cm2. This was tested in a microarthropod distribution study on the urban gradient of Riga city (Latvia) in six urban habitat types at 21 sites. The use of classical statistical methods for the processing of soil microarthropod data is limited because these data do not meet model requirements on which classical methods are based, first of all, conformity to the normal distribution. These problems are circumvented by bootstrapping methodology, which thanks to increasing computer performance now is implemented in the most modern program packages. We tested a set of such methods: one-way bootstrap-based analysis of variance, nonmetric multidimensional scaling (NMS), nonparametric multiplicative regression (NPMR), multi-response permutation procedure and Chao bootstrap-based rarefaction curves. NMS in combination with NPMR gave the best results providing statistically significant species distribution curves along the urban gradient which were broadly in line with species traits found by other studies. [ABSTRACT FROM AUTHOR]