Optimizing eDNA Metabarcoding Techniques for Assessing Arthropod Communities in Tree-Related Microhabitats

Abstract

Understanding the diversity and ecological roles of arthropods within tree-related microhabitats (TreMs) is crucial for forest ecosystem conservation and management. In our study, we aimed to identify the most effective environmental DNA (eDNA) metabarcoding approach for capturing ecologically important arthropod species primarily inhabiting the near-ground-level TreMs. We evaluated the use of COI and 16S primers for eDNA metabarcoding and compared direct and indirect eDNA sampling methods, including lying deadwood sediment sampling (LDS), standing deadwood sediment sampling (SDS), soil sampling (SS), and tree surface roller sampling (TSRS). Our results indicated significant biases and challenges, particularly in primer selection, with COI outperforming 16S in taxonomic resolution for most arthropod taxa. Our TSRS method effectively captured 408 OTUs at the species level, with the highest number of ecologically significant arthropods associated with TreMs compared to other approaches. Direct sampling from sediments revealed a higher abundance of fungi than arthropods, impacting diversity estimates. We also observed habitat-specific preferences among arthropods, with certain sampling methods capturing distinct taxa. Our findings underscore the importance of carefully selecting sampling methods and validating primers in eDNA metabarcoding studies and provide insights into the complexity of arthropod communities in TreMs. Optimized methods will advance monitoring techniques for forest ecosystems and inform conservation efforts to preserve arthropod diversity in TreMs.