Integrating Megabarcoding and Metabarcoding to Unlock Diversity and Distribution Data Shortfalls in Dark Taxa

Persistent biodiversity data shortfalls undermine our capacity to detect species, map their distributions and characterize their spatial genetic structure, limiting robust biogeographic analyses and the development of effective conservation strategies. This particularly affects hyperdiverse invertebrate groups where hidden diversity remains largely undocumented. This study develops and demonstrates the potential of an integrated high-throughput sequencing (HTS) framework to improve the representation of hidden diversity in regional species inventories and to help close critical gaps in our understanding of species distributions and genetic diversity from a conservation biogeography perspective. Focusing on the Canary Islands (Spain), the workflow combines megabarcoding of more than 4000 mesofauna specimens to generate a curated species-level molecular reference library with community DNA metabarcoding of 168 soil samples. This approach enables consistent taxonomic assignment across insular landscapes and increases the spatial and genetic resolution of occurrence data. We identified 145 species of mites and springtails, including 49 species newly recorded for the archipelago and numerous genetically distinct lineages likely representing undescribed taxa, highlighting all the biodiversity that remains to be described. Integration of the barcode library with metabarcoding data produced 1440 species occurrences, revealing extensive distributional gaps, multiple range expansions and strong within-island phylogeographic structuring, indicating prevalent diversification at fine spatial scales. These results highlight a deep, taxonomically broad underestimation of soil biodiversity and demonstrate that this integrative approach provides a transferable model for advancing the biogeography, evolutionary understanding and conservation of dark and cryptic taxa across broad taxonomic and conservation-relevant contexts.