Physical disruption of gene flow among mountains is commonly viewed as an important process for the generation of hyperdiverse tropical mountain biotas. However, the role of in situ diversification within mountains has been seldom explored. Here we evaluate spatially fine-scale patterns of arthropod community assembly within a single mountain to understand the role of dispersal limitation and landscape features as drivers of tropical mountain diversity. We focus on a single tropical sky-island of the Transmexican Volcanic Belt, where we sampled whole-communities of arthropods for eight orders with a comparable design at a spatial scale ranging from 50 m to 20 km, using 840 pitfall traps and whole community metabarcoding. We explored multiple hierarchical levels, from individual haplotypes to lineages at 0.5, 1.5, 3, 5, 7.5% similarity thresholds, to evaluate patterns of richness, turnover and distance decay of similarity with isolation-by-distance and isolation-by-resistance approaches. Our results showed that distance and altitude influence distance decay of similarity at all hierarchical levels. This holds for arthropod groups of contrasting dispersal abilities, but with different strength depending on the spatial scale. Our results suggest long-term persistence of lineages within sky islands, combined with local-scale differentiation, may be an important driver of high arthropod biodiversity in tropical mountains.

Our 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. This is due to inherent problems with obtaining high-quality arthropod data. Novel high throughput sequencing approaches are now emerging as powerful tools to overcome such limitations, and thus comprehensively address existing shortfalls in arthropod biodiversity data. Here we explore how, as a community, we might most effectively exploit these tools for comprehensive and comparable inventory and monitoring of insular arthropod biodiversity. We first review the strengths, limitations and potential synergies among existing approaches of high throughput barcode sequencing. We consider how this can be complemented with deep learning approaches applied to image analysis to study arthropod biodiversity. We then explore how these approaches can 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 identify seven island biology themes at the interface of ecology, evolution and conservation biology, within which collective and harmonised efforts in HTS arthropod inventory could yield significant advances in island biodiversity research.

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 eco-evolutionary 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 colonisation 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.

Metabarcoding of DNA extracted from community samples of whole organisms (whole organism community DNA, wocDNA) is increasingly being applied to terrestrial, marine and freshwater metazoan communities to provide rapid, accurate and high resolution data for novel molecular ecology research. The growth of this field has been accompanied by considerable development that builds on microbial metabarcoding methods to develop appropriate and efficient sampling and laboratory protocols for whole organism metazoan communities. However, considerably less attention has focused on ensuring bioinformatic methods are adapted and applied comprehensively in wocDNA metabarcoding. In this study we examined over 600 papers and identified 111 studies that performed COI metabarcoding of wocDNA. We then systematically reviewed the bioinformatic methods employed by these papers to identify the state-of-the-art. Our results show that the increasing use of wocDNA COI metabarcoding for metazoan diversity is characterised by a clear absence of bioinformatic harmonisation, and the temporal trends show little change in this situation. The reviewed literature showed (i) high heterogeneity across pipelines, tasks and tools used, (ii) limited or no adaptation of bioinformatic procedures to the nature of the COI fragment, and (iii) a worrying underreporting of tasks, software and parameters. Based upon these findings we propose a set of recommendations that we think the wocDNA metabarcoding community should consider to ensure that bioinformatic methods are appropriate, comprehensive and comparable. We believe that adhering to these recommendations will improve the long-term integrative potential of wocDNA COI metabarcoding for biodiversity science.