Microfauna community assembly and cascading relationship with microflora in cropland ecosystems along a latitudinal gradient

Cropland ecosystems are environmentally more homogeneous than natural ecosystems due to anthropogenic management. However, it is unclear whether there is similar convergence in soil fauna diversity and community assembly in croplands with different latitudes. Therefore, the study on the latitudinal pattern and community assembly processes of soil microfauna across a transect spanning 3200 km of croplands was conducted. The results indicated that the β diversity of plant parasites, fungivores, and bacterivores showed a decreasing trend and that of omnivores-predators at higher levels followed a unimodal distribution along a latitudinal gradient. The dissimilarity of soil microfauna communities increased with geographical distance, which exhibited a strong distance decay pattern. The β diversity partitioning analysis suggested that species replacement had the greatest influence for all trophic groups, except for omnivores-predators that were driven by a combination of richness differences and species replacement. The stochastic processes shaping the microfauna assembly prevailed over deterministic processes. Ecological drift and homogenizing dispersal of the stochastic processes accounted for 50.4% and 37% of total variations respectively, and heterogeneous selection of the deterministic processes for 10%. Both soil and climatic factors had a direct impact on soil microflora and plant parasites, and indirect impact on bacterivores, fungivores, and omnivores-predators through mediating microflora communities. The partial least squares path modeling and co-occurrence analysis all showed that the soil microfauna assembly was inextricably linked to soil microflora and their network complexity exhibited a significant increasing trend along the latitudinal gradient. Further studies are needed to optimize the molecular database of soil microfauna and construct models for predicting their community distribution patterns.