Paula Arribas

High‐throughput sequencing (HTS) allows large‐scale DNA barcoding of individually tagged specimens (‘megabarcoding’), but deep amplicon sequencing produces a mixture of authentic mitochondrial sequences together with nuclear pseudogenes (NUMTs), environmental and cross‐sample contaminants, and sequencing artefacts. Standard approaches relying on read clustering or dominant‐read selection often fail to classify these types, leading to incorrect taxonomic identifications and species counts. We developed an authentication framework by integrating abundance filtering, phylogenetic placement and taxonomic congruence. The workflow was applied to 18,533 morphospecies of tropical beetles (Coleoptera) from multiple biogeographic regions, which were imaged for family‐level identification, prior to individual Illumina barcoding. Sequencing yielded > 36 million reads and 64,544 unique ASVs, which were evaluated against a reference phylogeny of > 13,000 mitogenomes. Authentication succeeded for 86.5% of quality‐passing specimens (15,901 ASVs). Non‐authentic sequences were technical artefacts (58.0%), environmental contamination including prey DNA (14.2%), intra‐individual variants (NUMTs, heteroplasmy; 11.3%) and cross‐sample contamination (7.5%). Authentication success and the proportions of failure categories varied markedly across trap types, sampling campaigns, taxonomic groups and sequencing runs. We identified 930 confirmed NUMTs based on consistent co‐occurrence patterns and phylogenetic proximity to authenticated haplotypes. Single‐specimen HTS data contain substantial biological and technical complexity not resolved by standard filtering methods. Our pipeline‐agnostic, phylogenetically informed authentication framework achieves robust recovery of validated barcodes while retaining informative secondary variants, improving the accuracy of molecular ASV data to a standard sufficient for inclusion in barcode reference databases and the phylogenetically informed DNA barcoding of tropical insects.

Animal COI (mitochondrial cytochrome oxidase I) metabarcoding of environmental DNA (eDNA) is increasingly used to assess biodiversity in complex substrates such as soil. However, due to read-length constraints of second-generation sequencing platforms, mini-barcodes have been used instead of the full barcode region. Long-read sequencing technologies now enable the recovery of full-length barcode sequences, and are more commonly applied for studying microbes, but their use for metabarcoding the full-length standard COI barcoding region in animals remains limited. In this study, we compared three COI amplicon sets — 313 bp, 660 bp, and 1,256 bp — amplified from soil eDNA samples and sequenced using Illumina and PacBio platforms to evaluate their overall concurrence, the effectiveness of identifying nuclear mitochondrial DNA segments (NUMTs) and chimeras, as well as their respective taxonomic resolution. The long-read datasets exhibited a higher identification rate of NUMTs and true chimeras, suggesting that longer sequences improve the detection of noise in COI metabarcoding data, thereby reducing the occurrence of spurious taxa. Taxonomy assignment confidence was similar between the 313 bp and 660 bp datasets, whereas extending the amplicon beyond the standard COI barcode region (1,256 bp) reduced confidence, likely because longer reads extend into regions poorly represented in barcode reference databases. Despite substantially lower sequencing depth in the 660 bp dataset, per-sample OTU richness did not differ significantly from that recovered with the Illumina 313 bp amplicon set. Similarly, the relationships between samples were strongly correlated across the detected OTU communities, indicating consistent ecological interpretations between short and long amplicons. We conclude that the standard ~658 bp COI barcode is an optimal marker for soil animal metabarcoding from eDNA, balancing target recovery, artifact detection, taxonomic assignment and ecological interpretability. As COI eDNA metabarcoding becomes increasingly used in biodiversity assessment and is increasingly adopted in large-scale monitoring initiatives, this study provides methodological guidance for improving the robustness of soil animal community biomonitoring.

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.

The open ecosystem (e.g. grasslands, prairies, shrublands) tends to be ecologically less stable than closed one (i.e. forests) and encompassess higher spatial heterogeneity in terms of environmental diversity. Such differences are expected to differentially constrain the diversity and structure of the communities that inhabit each of them, but identifying the specific processes driving contrasting biodiversity patterns between open and closed systems is challenging. In order to understand how environmental variability might structure spider assemblages, both between and within open and closed ecosystems, we implement a high throughput multiplex barcode sequencing approach to generate a dataset for 8585 specimens representing 168 species, across the open ecosystem within the Canary Islands. Combining these with spider sequences from the closed ecosystem within the same islands, we show that spider communities in the open ecosystem show higher species richness, higher beta diversity, and higher proportions of rare species but proportionately lower numbers of endemic species than communities in the closed ecosystem. We furthermore assess if environmental heterogeneity and habitat stability are the major drivers of such differences by assessing spatial genetic structuring and the influence of bioclimatic variables. Our results point to environmental heterogeneity rather than stability as a major driver of spatial patterns between open and closed ecosystems.

1. The Canary Islands, a subtropical Spanish archipelago of volcanic origin, serve as the study’s focus, with a rich winemaking history dating back to the 16th century Spanish conquest (Alonso Gonz...

Soil arthropod diversity contributes to a high proportion of the total biodiversity on Earth. However, most soil arthropods are still undescribed, hindering our understanding of soil functioning and global biodiversity estimations. Inventorying soil arthropods using conventional taxonomical approaches is particularly difficult and costly due to the great species richness, abundance and local-scale heterogeneity of mesofauna communities and the poor taxonomic background knowledge of most lineages. To alleviate this situation, we have designed and implemented a molecular barcoding framework adapted to soil fauna. This pipeline includes different steps, starting with a morphology-based selection of specimens which are imaged. Then, DNA is extracted non-destructively. Both images and voucher specimens are used to assign a taxonomic identification, based on morphology that is further checked for consistency with molecular information. Using this procedure, we studied 239 specimens of mites from the Canary Islands including representatives of Mesostigmata, Sarcoptiformes and Trombidiformes, of which we recovered barcode sequences for 168 specimens that were morphologically identified to 49 species, with nine specimens that could only be identified at the genus or family levels. Multiple species delimitation analyses were run to compare molecular delimitations with morphological identifications, including ASAP, mlPTP, BINs and 3% and 8% genetic distance thresholds. Additionally, a species-level search was carried out at the Biodiversity Databank of the Canary Islands (BIOTA) to evaluate the number of species in our dataset that were not previously recorded in the archipelago. In parallel, a sequence-level search of our sequences was performed against BOLD Systems. Our results reveal that multiple morphologically identified species correspond to different molecular lineages, which points to significant levels of unknown cryptic diversity within the archipelago. In addition, we evidenced that multiple species in our dataset constituted new records for the Canary Islands fauna and that the information for these lineages within online genetic repositories is very incomplete. Our study represents the first systematic effort to catalogue the soil arthropod mesofauna of the Canary Islands and establishes the basis for the Canary Islands Soil Biodiversity barcode database. This resource will constitute a step forward in the knowledge of these arthropods in a region of special interest.

Soils harbour a rich arthropod fauna, but many species are still not formally described (Linnaean shortfall) and the distribution of those already described is poorly understood (Wallacean shortfall). Metabarcoding holds much promise to fill this gap, however, nuclear copies of mitochondrial genes, and other artefacts lead to taxonomic inflation, which compromise the reliability of biodiversity inventories. Here, we explore the potential of a bioinformatic approach to jointly “denoise” and filter nonauthentic mitochondrial sequences from metabarcode reads to obtain reliable soil beetle inventories and address open questions in soil biodiversity research, such as the scale of dispersal constraints in different soil layers. We sampled cloud forest arthropod communities from 49 sites in the Anaga peninsula of Tenerife (Canary Islands). We performed whole organism community DNA (wocDNA) metabarcoding, and built a local reference database with COI barcode sequences of 310 species of Coleoptera for filtering reads and the identification of metabarcoded species. This resulted in reliable haplotype data after considerably reducing nuclear mitochondrial copies and other artefacts. Comparing our results with previous beetle inventories, we found: (i) new species records, potentially representing undescribed species; (ii) new distribution records, and (iii) validated phylogeographic structure when compared with traditional sequencing approaches. Analyses also revealed evidence for higher dispersal constraint within deeper soil beetle communities, compared to those closer to the surface. The combined power of barcoding and metabarcoding contribute to mitigate the important shortfalls associated with soil arthropod diversity data, and thus address unresolved questions for this vast biodiversity fraction.

Current understanding of ecological and evolutionary processes underlying island biodiversity is heavily shaped by empirical data from plants and birds, although arthropods comprise the overwhelming majority of known animal species, and as such can provide key insights into processes governing biodiversity. Novel high throughput sequencing (HTS) approaches are now emerging as powerful tools to overcome limitations in the availability of arthropod biodiversity data, and hence provide insights into these processes. Here, we explored how these tools might be most effectively exploited for comprehensive and comparable inventory and monitoring of insular arthropod biodiversity. We first reviewed the strengths, limitations and potential synergies among existing approaches of high throughput barcode sequencing. We considered how this could be complemented with deep learning approaches applied to image analysis to study arthropod biodiversity. We then explored how these approaches could be implemented within the framework of an island Genomic Observatories Network (iGON) for the advancement of fundamental and applied understanding of island biodiversity. To this end, we identified seven island biology themes at the interface of ecology, evolution and conservation biology, within which collective and harmonized efforts in HTS arthropod inventory could yield significant advances in island biodiversity research.

Metazoan metabarcoding is emerging as an essential strategy for inventorying biodiversity, with diverse projects currently generating massive quantities of community-level data. The potential for integrating across such data sets offers new opportunities to better understand biodiversity and how it might respond to global change. However, large-scale syntheses may be compromised if metabarcoding workflows differ from each other. There are ongoing efforts to improve standardization for the reporting of inventory data. However, harmonization at the stage of generating metabarcode data has yet to be addressed. A modular framework for harmonized data generation offers a pathway to navigate the complex structure of terrestrial metazoan biodiversity. Here, through our collective expertise as practitioners, method developers, and researchers leading metabarcoding initiatives to inventory terrestrial biodiversity, we seek to initiate a harmonized framework for metabarcode data generation, with a terrestrial arthropod module. We develop an initial set of submodules covering the 5 main steps of metabarcode data generation: (i) sample acquisition; (ii) sample processing; (iii) DNA extraction; (iv) polymerase chain reaction amplification, library preparation, and sequencing; and (v) DNA sequence and metadata deposition, providing a backbone for a terrestrial arthropod module. To achieve this, we (i) identified key points for harmonization, (ii) reviewed the current state of the art, and (iii) distilled existing knowledge within submodules, thus promoting best practice by providing guidelines and recommendations to reduce the universe of methodological options. We advocate the adoption and further development of the terrestrial arthropod module. We further encourage the development of modules for other biodiversity fractions as an essential step toward large-scale biodiversity synthesis through harmonization.

Most of our understanding of island diversity comes from the study of aboveground systems, while the patterns and processes of diversification and community assembly for belowground biotas remain poorly understood. Here, we take advantage of a relatively young and dynamic oceanic island to advance our understanding of ecoevolutionary processes driving community assembly within soil mesofauna. Using whole organism community DNA (wocDNA) metabarcoding and the recently developed metaMATE pipeline, we have generated spatially explicit and reliable haplotype‐level DNA sequence data for soil mesofaunal assemblages sampled across the four main habitats within the island of Tenerife. Community ecological and metaphylogeographic analyses have been performed at multiple levels of genetic similarity, from haplotypes to species and supraspecific groupings. Broadly consistent patterns of local‐scale species richness across different insular habitats have been found, whereas local insular richness is lower than in continental settings. Our results reveal an important role for niche conservatism as a driver of insular community assembly of soil mesofauna, with only limited evidence for habitat shifts promoting diversification. Furthermore, support is found for a fundamental role of habitat in the assembly of soil mesofauna, where habitat specialism is mainly due to colonization and the establishment of preadapted species. Hierarchical patterns of distance decay at the community level and metaphylogeographical analyses support a pattern of geographic structuring over limited spatial scales, from the level of haplotypes through to species and lineages, as expected for taxa with strong dispersal limitations. Our results demonstrate the potential for wocDNA metabarcoding to advance our understanding of biodiversity.