Abstract:

Aims: Environmental DNA (eDNA) metabarcoding technology provides a novel approach for assessing soil arthropod diversity. This study aimed to compare the performance of three eDNA sampling methods for detecting soil arthropod. 

Methods: Soil samples were collected from eight crop fields. Three eDNA sampling methods were employed: direct soil extraction (SOL), air filtration (AIR), and water filtration (WAT). Arthropod community composition was analyzed using high-throughput sequencing. 

Results: No significant differences in alpha diversity were observed among the three methods; however, beta diversity differed significantly. The results of PERMANOVA indicated extremely significant differences in soil arthropod community structures among the three sampling methods (R² = 0.2816, P = 0.001). The sampling method accounted for 28.16% of the total variation in community composition. Furthermore, PCoA showed that samples from the three methods were distinctly separated along the ordination plot, forming three obvious clusters. SOL detected the highest number of OTUs (3,314), followed by AIR (1,023) and WAT (871). At the family level, SOL showed a clear advantage in detecting soil-dwelling groups such as Isotomidae; WAT exhibited the highest relative abundance of Chironomidae (exceeding 95% in some samples); AIR demonstrated superior detection efficiency for Scarabaeidae. Among natural enemy groups, Staphylinidae and Empididae were detected in all three methods, and Thomisidae and Oonopidae were detected only by SOL. Network analysis revealed dense OTU clusters around SOL nodes in SOL vs. AIR and SOL vs. WAT comparisons, while in the AIR vs. WAT comparison, high-abundance OTUs were largely method-specific. Rank occurrence curves indicated that SOL detected the most species (169) with the most even distribution, followed by WAT (113) and AIR (83), with AIR dominated by a few abundant species. 

Conclusions: This study clarifies that the distribution of eDNA in the solid, gaseous, and liquid phases of soil is closely related to the ecological niche and behavioral types of arthropods, exhibiting significant distributional heterogeneity. SOL provides stable and broad-spectrum detection for soil-dwelling groups and various natural enemy taxa. AIR shows advantages in detecting groups such as Diptera and Scarabaeidae. WAT is particularly effective in enriching taxa like Chironomidae that prefer moist environments. For biodiversity assessment of farmland soil, the SOL method is recommended as the foundation. If the research focuses on specific taxa such as Diptera or Coleoptera, the AIR method can be added as a supplement to SOL. If the study involves taxa that prefer moist environments, such as Chironomidae, the WAT method should be additionally incorporated. This study provides a scientific basis for understanding the spatial distribution characteristics of eDNA in soil ecosystems and for the selection and optimization of methods for monitoring soil animal diversity in agricultural fields.

Key words: environmental DNA, soil arthropods, agroecosystem, biodiversity monitoring, DNA metabarcoding